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added more augmentations to finally beat sota 

- class_bert_augmentation is now the reference training code
This commit is contained in:
Richard Wong 2025-01-15 20:09:15 +09:00
parent e90bc69ea9
commit 5312cfa06f
32 changed files with 2837 additions and 235 deletions
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41
analysis/corrupt_text.py Normal file
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@ -0,0 +1,41 @@
# %%
import random
import string
def corrupt_word(word):
"""Corrupt a single word using random corruption techniques."""
if len(word) <= 1: # Skip corruption for single-character words
return word
corruption_type = random.choice(["delete", "swap"])
if corruption_type == "delete":
# Randomly delete a character
idx = random.randint(0, len(word) - 1)
word = word[:idx] + word[idx + 1:]
elif corruption_type == "swap":
# Swap two adjacent characters
if len(word) > 1:
idx = random.randint(0, len(word) - 2)
word = (word[:idx] + word[idx + 1] + word[idx] + word[idx + 2:])
return word
def corrupt_string(sentence, corruption_probability=0.01):
"""Corrupt each word in the string with a given probability."""
words = sentence.split()
corrupted_words = [
corrupt_word(word) if random.random() < corruption_probability else word
for word in words
]
return " ".join(corrupted_words)
# Example usage
sentence = "This is a simple string for testing"
corrupted_sentence = corrupt_string(sentence, corruption_probability=0.1)
print("Original:", sentence)
print("Corrupted:", corrupted_sentence)
# %%

95
analysis/entity_hierarchy.py
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@ -1,95 +0,0 @@
# %%
import json
import pandas as pd
##########################################
# %%
# Load the JSON file
data_path = '../esAppMod/tca_entities.json'
with open(data_path, 'r') as file:
data = json.load(file)
# Initialize an empty list to store the rows
rows = []
# %%
# Loop through all entities in the JSON
for entity in data["data"].items():
entity_data = entity[1]
entity_id = entity_data['entity_id']
entity_name = entity_data['entity_name']
entity_type_id = entity_data['entity_type_id']
entity_type_name = entity_data['entity_type_name']
# Add each mention and its entity_id to the rows list
rows.append(
{
'id': entity_id,
'name': entity_name,
'type_id': entity_type_id,
'type_name': entity_type_name
})
# Create a DataFrame from the rows
df = pd.DataFrame(rows)
# %%
# df.to_csv('entity.csv', index=False)
df
# %%
df['type_name'].value_counts()
# %%
df['type_id'].value_counts()
# %%
name_list = df['name'].to_list()
# %%
name_list
# %%
from scipy.cluster.hierarchy import dendrogram, linkage, fcluster
import numpy as np
# %%
# Define labels
labels = name_list
# Create a prefix-based distance matrix
def prefix_distance(label1, label2):
prefix1 = label1.split()
prefix2 = label2.split()
# Find common prefix length
common_prefix_length = len([w1 for w1, w2 in zip(prefix1, prefix2) if w1 == w2])
# Distance is inversely proportional to common prefix length
return 1.0 / (common_prefix_length + 1)
# Create a pairwise distance matrix
n = len(labels)
distance_matrix = np.zeros((n, n))
for i in range(n):
for j in range(n):
distance_matrix[i, j] = prefix_distance(labels[i], labels[j])
# Perform hierarchical clustering
linkage_matrix = linkage(distance_matrix, method='average')
# Visualize as a dendrogram
import matplotlib.pyplot as plt
dendrogram(linkage_matrix, labels=labels, leaf_rotation=90, leaf_font_size=2)
plt.title("Prefix-Based Clustering")
plt.show()
# %%
linkage_matrix
# %%
# Extract flat clusters with a distance threshold
threshold = 0.5
clusters = fcluster(linkage_matrix, t=threshold, criterion='distance')
# Display clusters
for i, cluster_id in enumerate(clusters):
print(f"Label: {labels[i]}, Cluster ID: {cluster_id}")
# %%

33
analysis/error_analysis.py
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@ -3,53 +3,55 @@ import pandas as pd
# %%
# import training file
data_path = '../data_import/train.csv'
data_path = '../esAppMod_data_import/train.csv'
# data_path = '../esAppMod_data_import/parent_train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# import test file
data_path = '../data_import/test.csv'
data_path = '../esAppMod_data_import/test.csv'
# data_path = '../esAppMod_data_import/parent_test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
# import entity file
data_path = '../data_import/entity.csv'
data_path = '../esAppMod_data_import/entity.csv'
entity_df = pd.read_csv(data_path, skipinitialspace=True)
id2label = {}
for _, row in entity_df.iterrows():
id2label[row['id']] = row['name']
# %%
train_df.sort_values(by=['entity_id']).to_markdown('out.md')
# %%
data_path = '../train/class_bert_process/prediction/exports/result.csv'
data_path = '../train/class_bert_augmentation/prediction/exports/result.csv'
prediction_df = pd.read_csv(data_path)
# %%
predicted_entity_list = []
for element in prediction_df['class_prediction']:
predicted_entity_list.append(id2label[element])
prediction_df['predicted_name'] = predicted_entity_list
# %%
new_df = pd.concat((test_df, prediction_df ), axis=1)
# %%
mismatch_mask = new_df['entity_id'] != new_df['class_prediction']
mismatch_df = new_df[mismatch_mask]
# %%
len(mismatch_df)
# %%
# print the top 10 offending classes
# mask1 = mismatch_df['entity_id'] != 434
# mask2 = mismatch_df['entity_id'] != 451
# mask3 = mismatch_df['entity_id'] != 452
# mask= mask1 & mask2 & mask3
# masked_df = mismatch_df[mask]
# print(masked_df['entity_id'].value_counts()[:10])
print(mismatch_df['entity_id'].value_counts()[:10])
masked_df = mismatch_df
# %%
# Convert the whole dataframe as a string and display
# print the mismatch_df
print(mismatch_df.sort_values(by=['entity_id']).to_markdown())
print(masked_df.sort_values(by=['entity_id']).to_markdown())
# %%
mismatch_df.to_csv('error.csv')
@ -62,14 +64,9 @@ mismatch_df[select_mask]
# %%
# let us see the train mentions
select_value = 452
select_value = 130
select_mask = train_df['entity_id'] == select_value
train_df[select_mask]
# %%
mismatch_df[select_mask]['class_prediction'].to_list()
# %%
# %%

62
analysis/label_acronym.py Normal file
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@ -0,0 +1,62 @@
# %%
import pandas as pd
import re
# %%
# import training file
data_path = '../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# import test file
data_path = '../esAppMod_data_import/test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
# import entity file
data_path = '../esAppMod_data_import/entity.csv'
entity_df = pd.read_csv(data_path, skipinitialspace=True)
id2label = {}
for _, row in entity_df.iterrows():
id2label[row['id']] = row['name']
# %%
train_df
# %%
def extract_acronym_mapping(names):
mapping = {}
for name in names:
# Find acronym in parentheses
match = re.search(r"\((\w+)\)", name)
if match:
acronym = match.group(1)
# Remove unrelated prepended terms
core_term = re.sub(r"^([\w\s]+)\s*\(\w+\)$", r"\1", name).strip()
# Add to dictionary
mapping[acronym] = core_term
return mapping
names = set(train_df['entity_name'].to_list())
# Extract mappings
acronym_mapping = extract_acronym_mapping(names)
print(acronym_mapping)
# %%
del acronym_mapping['E'] # too many false matches
acronym_mapping = {key.lower():value.lower() for key, value in acronym_mapping.items()}
abbrev_to_term = {rf'\b{key}\b': value for key, value in acronym_mapping.items()}
term_to_abbrev = {rf'\b{value}\b': key for key, value in acronym_mapping.items()}
# %%
abbrev_to_term
# %%
term_to_abbrev
# %%
acronym_mapping
# %%

5
esAppMod_data_import/.gitignore vendored
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@ -0,0 +1,5 @@
out.md
parent_test.csv
parent_train.csv
test_seq.csv
train_seq.csv

124
esAppMod_data_import/entity_hierarchy.py Normal file
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# %%
import json
import pandas as pd
##########################################
# %%
# import training file
data_path = '../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# %%
# import entity file
# Keep only one row per unique value in 'column1'
unique_df = train_df.drop_duplicates(subset="entity_name", keep="first")
id2label = {}
for _, row in unique_df.iterrows():
id2label[row['entity_id']] = row['entity_name']
inverse_dict = {value:key for key,value in id2label.items()}
# %%
# Create a new dictionary with sorted keys
# sorted_dict = {key: id2label[key] for key in sorted(id2label.keys())}
sorted_dict = {key: inverse_dict[key] for key in sorted(inverse_dict.keys())}
# %%
sorted_dict
# %%
rule_set ={
'.NET': [497,482,484,487,485,486,483],
'apache': [6,634,501,646,259,7,8,9,375,697,10,11,12,260,376],
'C++': [583,306],
'CA': [290,22,23,24,25],
'CSS': [307,377],
'Cisco': [28,420,29],
'Citrix': [563,565,31,292,291,564,32,30],
'coldfusion': [311,37],
'eclipse': [46,622,641,456],
'xml': [596, 318],
'xsl': [319,320],
'HP': [59,293,60,61,58],
'http': [505,543],
'IBM': [698,63,64,649,65,666,294,66,265,328,67,330,68,458,69,70,71,72,672,73,295,250,605],
'IBM BigFix': [62,457],
'IBM ILOG': [253,255,254,256,252],
'IBM Tivoli': [606,459,76,77,604,460,461,462,463,79],
'IBM WebSphere': [80,82,83,81],
'IBM i': [424,329],
'IDMS': [667,668],
'IIS': [609,490,489,491],
'JBoss': [268,492,493],
'JavaScript': [589,405,406,407,408,409,411,412,413,415,410,414],
'Java': [506,523,584,378,379,380,381,384,382,383,385,386,387,392,393,388,333,389,334,390,391,335,336,394,395,396,397,398,399,400,401,402,403,404],
'KVS': [549,550,551],
'Linux': [576,454,427,428,429,453,430,432,433,434,435,436,431,437],
'MS SQL': [581,121,466,467,465,468,469,470,471,472,473],
'MVS': [577,440,441],
'Microsoft': [99,637,100,101,102,103,104,464,105,108,106,107,109,110,111,112,113,114],
'Oracle': [130,131,129,132,133,135,136,298,137,140,694,141,289,675,142,145,146,143,144,147,567,148,527,281],
'Oracle WebLogic': [600,233],
'Oracle Application Server': [610,494],
'Oracle Database': [134,474,475,478],
'Oracle Hyperion': [607,138,139],
'Oracle WebCenter': [276,495],
'Pascal': [599,346],
'Perl': [585,348,417,349],
'ProjectWise': [161,162],
'Rational': [166,167],
'SAP': [173,175,695,176,676,178,179],
'SAP ERP': [174,476,477],
'SAP NetWeaver': [279,496,177],
'Sybase SQL Server': [190,479,480],
'Sysinternal Tools': [194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212],
'TIBCO': [218,219],
'TIBCO Business Works': [217,481],
'Tivoli': [220,251],
'Tortoise': [221,222],
'Unix': [578,445,579,447,602,590,448,449],
'VB': [368,369],
'VMware': [568,569,229,230,231],
'Visual Basic': [370,371,372],
'WebSphere': [234,285,235,286,284,601,287],
'Windows': [580,238,239,451,452],
'z': [598,608,591]
}
# %%
# iterate through the whole training set
new_df = train_df.copy()
for idx, row in train_df.iterrows():
# we iterate through each rule set, replacing any matching values in the
# list with the first element of the list
for key in rule_set.keys():
id = row['entity_id']
if (id in rule_set[key]):
new_df.loc[idx,('entity_id')] = rule_set[key][0]
# %%
len(set(new_df['entity_id'].to_list()))
# %%
new_df.to_csv('parent_train.csv')
# %%
# now do the same for the test data
# import training file
data_path = '../esAppMod_data_import/test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
new_df = test_df.copy()
for idx, row in test_df.iterrows():
# we iterate through each rule set, replacing any matching values in the
# list with the first element of the list
for key in rule_set.keys():
id = row['entity_id']
if (id in rule_set[key]):
new_df.loc[idx,('entity_id')] = rule_set[key][0]
# %%
new_df
# %%
new_df.to_csv('parent_test.csv')
# %%

129
esAppMod_data_import/entity_hierarchy_for_seq2seq.py Normal file
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@ -0,0 +1,129 @@
# %%
import json
import pandas as pd
##########################################
# %%
# import training file
data_path = '../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# %%
# import entity file
# Keep only one row per unique value in 'column1'
unique_df = train_df.drop_duplicates(subset="entity_name", keep="first")
id2label = {}
for _, row in unique_df.iterrows():
id2label[row['entity_id']] = row['entity_name']
inverse_dict = {value:key for key,value in id2label.items()}
# %%
# Create a new dictionary with sorted keys
# sorted_dict = {key: id2label[key] for key in sorted(id2label.keys())}
sorted_dict = {key: inverse_dict[key] for key in sorted(inverse_dict.keys())}
# %%
sorted_dict
# %%
rule_set ={
'.NET': [497,482,484,487,485,486,483],
'apache': [6,634,501,646,259,7,8,9,375,697,10,11,12,260,376],
'C++': [583,306],
'CA': [290,22,23,24,25],
'CSS': [307,377],
'Cisco': [28,420,29],
'Citrix': [563,565,31,292,291,564,32,30],
'coldfusion': [311,37],
'eclipse': [46,622,641,456],
'xml': [596, 318],
'xsl': [319,320],
'HP': [59,293,60,61,58],
'http': [505,543],
'IBM': [698,63,64,649,65,666,294,66,265,328,67,330,68,458,69,70,71,72,672,73,295,250,605],
'IBM BigFix': [62,457],
'IBM ILOG': [253,255,254,256,252],
'IBM Tivoli': [606,459,76,77,604,460,461,462,463,79],
'IBM WebSphere': [80,82,83,81],
'IBM i': [424,329],
'IDMS': [667,668],
'IIS': [609,490,489,491],
'JBoss': [268,492,493],
'JavaScript': [589,405,406,407,408,409,411,412,413,415,410,414],
'Java': [506,523,584,378,379,380,381,384,382,383,385,386,387,392,393,388,333,389,334,390,391,335,336,394,395,396,397,398,399,400,401,402,403,404],
'KVS': [549,550,551],
'Linux': [576,454,427,428,429,453,430,432,433,434,435,436,431,437],
'MS SQL': [581,121,466,467,465,468,469,470,471,472,473],
'MVS': [577,440,441],
'Microsoft': [99,637,100,101,102,103,104,464,105,108,106,107,109,110,111,112,113,114],
'Oracle': [130,131,129,132,133,135,136,298,137,140,694,141,289,675,142,145,146,143,144,147,567,148,527,281],
'Oracle WebLogic': [600,233],
'Oracle Application Server': [610,494],
'Oracle Database': [134,474,475,478],
'Oracle Hyperion': [607,138,139],
'Oracle WebCenter': [276,495],
'Pascal': [599,346],
'Perl': [585,348,417,349],
'ProjectWise': [161,162],
'Rational': [166,167],
'SAP': [173,175,695,176,676,178,179],
'SAP ERP': [174,476,477],
'SAP NetWeaver': [279,496,177],
'Sybase SQL Server': [190,479,480],
'Sysinternal Tools': [194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212],
'TIBCO': [218,219],
'TIBCO Business Works': [217,481],
'Tivoli': [220,251],
'Tortoise': [221,222],
'Unix': [578,445,579,447,602,590,448,449],
'VB': [368,369],
'VMware': [568,569,229,230,231],
'Visual Basic': [370,371,372],
'WebSphere': [234,285,235,286,284,601,287],
'Windows': [580,238,239,451,452],
'z': [598,608,591]
}
# %%
# iterate through the whole training set
new_df = train_df.copy()
for idx, row in train_df.iterrows():
# we iterate through each rule set, replacing any matching values in the
# list with the first element of the list
for key in rule_set.keys():
id = row['entity_id']
if (id in rule_set[key]):
stem = rule_set[key][0]
leaf = rule_set[key].index(id)
new_df.loc[idx,('entity_seq')] = f"{stem}_{leaf}"
# %%
len(set(new_df['entity_seq'].to_list()))
# %%
new_df.to_csv('train_seq.csv')
# %%
# now do the same for the test data
# import training file
data_path = '../esAppMod_data_import/test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
new_df = test_df.copy()
for idx, row in test_df.iterrows():
# we iterate through each rule set, replacing any matching values in the
# list with the first element of the list
for key in rule_set.keys():
id = row['entity_id']
if (id in rule_set[key]):
stem = rule_set[key][0]
leaf = rule_set[key].index(id)
new_df.loc[idx,('entity_seq')] = f"{stem}_{leaf}"
# %%
new_df
# %%
new_df.to_csv('test_seq.csv')
# %%

0
train/class_bert_process/.gitignore → train/class_bert_augmentation/.gitignore vendored
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0
train/class_bert_process/prediction/.gitignore → train/class_bert_augmentation/prediction/.gitignore vendored
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8
train/class_bert_process/prediction/output.txt → train/class_bert_augmentation/prediction/output.txt
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@ -1,6 +1,6 @@
*******************************************************************************
Accuracy: 0.77655
F1 Score: 0.79605
Precision: 0.85637
Recall: 0.77655
Accuracy: 0.80197
F1 Score: 0.81948
Precision: 0.88067
Recall: 0.80197

15
train/class_bert_process/prediction/predict.py → train/class_bert_augmentation/prediction/predict.py
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@ -32,6 +32,8 @@ torch.set_float32_matmul_precision('high')
BATCH_SIZE = 256
# %%
# construct the target id list
# data_path = '../../../esAppMod_data_import/train.csv'
data_path = '../../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# rather than use pattern, we use the real thing and property
@ -52,19 +54,8 @@ def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Remove any non alphanumeric character
# text = re.sub(r'[^\w\s]', ' ', text) # Retains only alphanumeric and spaces
text = re.sub(r"[-;:]", " ", text)
# Add space between digit followed by a letter
text = re.sub(r"(\d)([A-Z])", r"\1 \2", text)
# Add space between letter followed by a digit
text = re.sub(r"([A-Z])(\d)", r"\1 \2", text)
# Substitute digits with '#'
text = re.sub(r'\d+', 'x', text)
# text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()

562
train/class_bert_augmentation/train.py Normal file
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@ -0,0 +1,562 @@
# %%
# from datasets import load_from_disk
import os
os.environ['NCCL_P2P_DISABLE'] = '1'
os.environ['NCCL_IB_DISABLE'] = '1'
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
import re
import random
import torch
from transformers import (
AutoTokenizer,
AutoModelForSequenceClassification,
DataCollatorWithPadding,
Trainer,
EarlyStoppingCallback,
TrainingArguments
)
import evaluate
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
from datasets import Dataset, DatasetDict
torch.set_float32_matmul_precision('high')
# %%
def set_seed(seed):
"""
Set the random seed for reproducibility.
"""
random.seed(seed) # Python random module
np.random.seed(seed) # NumPy random
torch.manual_seed(seed) # PyTorch CPU
torch.cuda.manual_seed(seed) # PyTorch GPU
torch.cuda.manual_seed_all(seed) # If using multiple GPUs
torch.backends.cudnn.deterministic = True # Ensure deterministic behavior
torch.backends.cudnn.benchmark = False # Disable optimization for reproducibility
set_seed(42)
SHUFFLES=10
# %%
# import training file
data_path = '../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# rather than use pattern, we use the real thing and property
entity_ids = train_df['entity_id'].to_list()
target_id_list = sorted(list(set(entity_ids)))
# %%
id2label = {}
label2id = {}
for idx, val in enumerate(target_id_list):
id2label[idx] = val
label2id[val] = idx
# %%
# introduce pre-processing functions
def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Substitute digits with 'x'
# text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()
return text
def generate_random_shuffles(text, n):
"""
Generate n strings with randomly shuffled words from the input text.
Args:
text (str): The input text.
n (int): The number of random variations to generate.
Returns:
list: A list of strings with shuffled words.
"""
words = text.split() # Split the input into words
shuffled_variations = []
for _ in range(n):
shuffled = words[:] # Copy the word list to avoid in-place modification
random.shuffle(shuffled) # Randomly shuffle the words
shuffled_variations.append(" ".join(shuffled)) # Join the words back into a string
return shuffled_variations
# generate n more shuffled examples
def shuffle_text(text, n_shuffles=SHUFFLES):
"""
Preprocess a list of texts and add n random shuffles for each string.
Args:
texts (list): An input strings.
n_shuffles (int): Number of random shuffles to generate for each string.
Returns:
list: A list of preprocessed and shuffled strings.
"""
all_processed = []
# add the original text
all_processed.append(text)
# Generate random shuffles
shuffled_variations = generate_random_shuffles(text, n_shuffles)
all_processed.extend(shuffled_variations)
return all_processed
acronym_mapping = {
'hpsa': 'hp server automation',
'tam': 'tivoli access manager',
'adf': 'application development facility',
'html': 'hypertext markup language',
'wff': 'microsoft web farm framework',
'jsp': 'javaserver pages',
'bw': 'business works',
'ssrs': 'sql server reporting services',
'cl': 'control language',
'vba': 'visual basic for applications',
'esapi': 'enterprise security api',
'gwt': 'google web toolkit',
'pki': 'perkin elmer informatics',
'rtd': 'oracle realtime decisions',
'jms': 'java message service',
'db': 'database',
'soa': 'service oriented architecture',
'xsl': 'extensible stylesheet language',
'com': 'compopent object model',
'ldap': 'lightweight directory access protocol',
'odm': 'ibm operational decision manager',
'soql': 'salesforce object query language',
'oms': 'order management system',
'cfml': 'coldfusion markup language',
'nas': 'netscape application server',
'sql': 'structured query language',
'bde': 'borland database engine',
'imap': 'internet message access protocol',
'uws': 'ultidev web server',
'birt': 'business intelligence and reporting tools',
'mdw': 'model driven workflow',
'tws': 'tivoli workload scheduler',
'jre': 'java runtime environment',
'wcs': 'websphere commerce suite',
'was': 'websphere application server',
'ssis': 'sql server integration services',
'xhtml': 'extensible hypertext markup language',
'soap': 'simple object access protocol',
'san': 'storage area network',
'elk': 'elastic stack',
'arr': 'application request routing',
'xlst': 'extensible stylesheet language transformations',
'sccm': 'microsoft endpoint configuration manager',
'ejb': 'enterprise java beans',
'css': 'cascading style sheets',
'hpoo': 'hp operations orchestration',
'xml': 'extensible markup language',
'esb': 'enterprise service bus',
'edi': 'electronic data interchange',
'imsva': 'interscan messaging security virtual appliance',
'wtx': 'ibm websphere transformation extender',
'cgi': 'common gateway interface',
'bal': 'ibm basic assembly language',
'issow': 'integrated safe system of work',
'dcl': 'data control language',
'jdom': 'java document object model',
'fim': 'microsoft forefront identity manager',
'npl': 'niakwa programming language',
'wf': 'windows workflow foundation',
'lm': 'etap license manager',
'wts': 'windows terminal server',
'asp': 'active server pages',
'jil': 'job information language',
'mvc': 'model view controller',
'rmi': 'remote method invocation',
'ad': 'active directory',
'owb': 'oracle warehouse builder',
'rest': 'representational state transfer',
'jdk': 'java development kit',
'ids': 'integrated data store',
'bms': 'batch management software',
'vsx': 'vmware solution exchange',
'ssas': 'sql server analysis services',
'atl': 'atlas transformation language',
'ice': 'infobright community edition',
'esql': 'extended structured query language',
'corba': 'common object request broker architecture',
'dpe': 'device provisioning engines',
'rac': 'oracle real application clusters',
'iemt': 'iis easy migration tool',
'mes': 'manufacturing execution system',
'odbc': 'open database connectivity',
'lms': 'lan management solution',
'wcf': 'windows communication foundation',
'nes': 'netscape enterprise server',
'jsf': 'javaserver faces',
'alm': 'application lifecycle management',
'hlasm': 'high level assembler',
'cmod': 'content manager ondemand'}
external_source = {
'vb.net': 'visual basic dot net',
'jes': 'job entry subsystem',
'svn': 'subversion',
'vcs': 'version control system',
'lims': 'laboratory information management system',
'ide': 'integrated development environment',
'sdk': 'software development kit',
'mq': 'message queue',
'ims': 'information management system',
'isa': 'internet security and acceleration',
'vs': 'visual studio',
'esr': 'extended support release',
'ff': 'firefox',
'vb': 'visual basic',
'rhel': 'red hat enterprise linux',
'iis': 'internet information server',
'api': 'application programming interface',
'se': 'standard edition',
'\.net': 'dot net',
'c#': 'c sharp'
}
# synonyms = {
# 'windows server': 'windows nt',
# 'windows 7': 'windows desktop',
# 'windows 8': 'windows desktop',
# 'windows 10': 'windows desktop'
# }
# add more information
acronym_mapping.update(external_source)
abbrev_to_term = {f'\b{key}\b': value for key, value in acronym_mapping.items()}
term_to_abbrev = {f'\b{value}\b': key for key, value in acronym_mapping.items()}
def replace_terms_with_abbreviations(text):
for input, replacement in term_to_abbrev.items():
text = re.sub(input, replacement, text)
return text
def replace_abbreviations_with_terms(text):
for input, replacement in abbrev_to_term.items():
text = re.sub(input, replacement, text)
return text
######################################
# augmentation by text corruption
def corrupt_word(word):
"""Corrupt a single word using random corruption techniques."""
if len(word) <= 1: # Skip corruption for single-character words
return word
corruption_type = random.choice(["delete", "swap"])
if corruption_type == "delete":
# Randomly delete a character
idx = random.randint(0, len(word) - 1)
word = word[:idx] + word[idx + 1:]
elif corruption_type == "swap":
# Swap two adjacent characters
if len(word) > 1:
idx = random.randint(0, len(word) - 2)
word = (word[:idx] + word[idx + 1] + word[idx] + word[idx + 2:])
return word
def corrupt_string(sentence, corruption_probability=0.01):
"""Corrupt each word in the string with a given probability."""
words = sentence.split()
corrupted_words = [
corrupt_word(word) if random.random() < corruption_probability else word
for word in words
]
return " ".join(corrupted_words)
# outputs a list of dictionaries
# processes dataframe into lists of dictionaries
# each element maps input to output
# input: tag_description
# output: class label
label_flag_list = []
def process_df_to_dict(df):
output_list = []
for _, row in df.iterrows():
# produce shuffling
index = row['entity_id']
parent_desc = row['mention']
parent_desc = preprocess_text(parent_desc)
# Split the string into words
words = parent_desc.split()
# Count the number of words
word_count = len(words)
# short sequences are rare, and we must compensate by including more examples
# mutation of other longer sequences might drown out rare short sequences
if word_count < 3:
for _ in range(10):
element = {
'text': parent_desc,
'label': label2id[index],
}
output_list.append(element)
# check if label is in label_flag_list
if index not in label_flag_list:
entity_name = row['entity_name']
# add the "entity_name" label as a mention
element = {
'text': entity_name,
'label': label2id[index],
}
output_list.append(element)
# remove all non-alphanumerics
desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# add shufles of the original entity name
no_of_shuffles = SHUFFLES
processed_descs = shuffle_text(entity_name, n_shuffles=no_of_shuffles)
for desc in processed_descs:
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
label_flag_list.append(index)
# add shuffled strings
processed_descs = shuffle_text(parent_desc, n_shuffles=SHUFFLES)
for desc in processed_descs:
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# corrupt string
desc = corrupt_string(parent_desc, corruption_probability=0.1)
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# remove all non-alphanumerics
desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# # augmentation
# # perform abbrev_to_term
# temp_desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
# desc = replace_terms_with_abbreviations(temp_desc)
# if (desc != temp_desc):
# element = {
# 'text' : desc,
# 'label': label2id[index], # ensure labels starts from 0
# }
# output_list.append(element)
# augmentation
# perform term to abbrev
desc = replace_abbreviations_with_terms(parent_desc)
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
return output_list
def create_dataset():
# train
data_path = '../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
combined_data = DatasetDict({
'train': Dataset.from_list(process_df_to_dict(train_df)),
})
return combined_data
# %%
def train():
save_path = f'checkpoint'
split_datasets = create_dataset()
# prepare tokenizer
model_checkpoint = "distilbert/distilbert-base-uncased"
# model_checkpoint = 'google-bert/bert-base-cased'
# model_checkpoint = 'prajjwal1/bert-small'
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, return_tensors="pt", clean_up_tokenization_spaces=True)
# Define additional special tokens
# additional_special_tokens = ["<DESC>"]
# Add the additional special tokens to the tokenizer
# tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
max_length = 120
# given a dataset entry, run it through the tokenizer
def preprocess_function(example):
input = example['text']
# text_target sets the corresponding label to inputs
# there is no need to create a separate 'labels'
model_inputs = tokenizer(
input,
max_length=max_length,
truncation=True,
padding=True
)
return model_inputs
# map maps function to each "row" in the dataset
# aka the data in the immediate nesting
tokenized_datasets = split_datasets.map(
preprocess_function,
batched=True,
num_proc=8,
remove_columns="text",
)
# %% temp
# tokenized_datasets['train'].rename_columns()
# %%
# create data collator
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
# %%
# compute metrics
metric = evaluate.load("accuracy")
def compute_metrics(eval_preds):
preds, labels = eval_preds
preds = np.argmax(preds, axis=1)
return metric.compute(predictions=preds, references=labels)
# %%
# create id2label and label2id
# %%
model = AutoModelForSequenceClassification.from_pretrained(
model_checkpoint,
num_labels=len(target_id_list),
id2label=id2label,
label2id=label2id)
# important! after extending tokens vocab
model.resize_token_embeddings(len(tokenizer))
# model = torch.compile(model, backend="inductor", dynamic=True)
# %%
# Trainer
training_args = TrainingArguments(
output_dir=f"{save_path}",
# eval_strategy="epoch",
eval_strategy="no",
logging_dir="tensorboard-log",
logging_strategy="epoch",
# save_strategy="epoch",
load_best_model_at_end=False,
learning_rate=5e-5,
per_device_train_batch_size=64,
per_device_eval_batch_size=64,
auto_find_batch_size=False,
ddp_find_unused_parameters=False,
weight_decay=0.01,
save_total_limit=1,
num_train_epochs=40,
warmup_steps=400,
bf16=True,
push_to_hub=False,
remove_unused_columns=False,
)
trainer = Trainer(
model,
training_args,
train_dataset=tokenized_datasets["train"],
tokenizer=tokenizer,
data_collator=data_collator,
compute_metrics=compute_metrics,
# callbacks=[EarlyStoppingCallback(early_stopping_patience=3)],
)
# uncomment to load training from checkpoint
# checkpoint_path = 'default_40_1/checkpoint-5600'
# trainer.train(resume_from_checkpoint=checkpoint_path)
trainer.train()
# execute training
train()
# %%

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tensorboard-log

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*******************************************************************************
Accuracy: 0.71956
F1 Score: 0.74142
Precision: 0.81529
Recall: 0.71956
********************************************************************************
Accuracy: 0.71710
F1 Score: 0.74095
Precision: 0.82181
Recall: 0.71710

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*******************************************************************************
Accuracy: 0.81591
F1 Score: 0.82162
Precision: 0.85519
Recall: 0.81591

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*******************************************************************************
Accuracy: 0.59943
F1 Score: 0.60266
Precision: 0.66956
Recall: 0.59943

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# %%
# from datasets import load_from_disk
import os
import glob
os.environ['NCCL_P2P_DISABLE'] = '1'
os.environ['NCCL_IB_DISABLE'] = '1'
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
import re
import torch
from torch.utils.data import DataLoader
from transformers import (
AutoTokenizer,
AutoModelForSequenceClassification,
DataCollatorWithPadding,
)
import evaluate
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
from datasets import Dataset, DatasetDict
from tqdm import tqdm
torch.set_float32_matmul_precision('high')
BATCH_SIZE = 256
# %%
# construct the target id list
# data_path = '../../../esAppMod_data_import/train.csv'
data_path = '../../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# rather than use pattern, we use the real thing and property
entity_ids = train_df['entity_id'].to_list()
target_id_list = sorted(list(set(entity_ids)))
# %%
id2label = {}
label2id = {}
for idx, val in enumerate(target_id_list):
id2label[idx] = val
label2id[val] = idx
# introduce pre-processing functions
def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Substitute digits with '#'
text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()
return text
# outputs a list of dictionaries
# processes dataframe into lists of dictionaries
# each element maps input to output
# input: tag_description
# output: class label
def process_df_to_dict(df):
output_list = []
for _, row in df.iterrows():
desc = row['mention']
desc = preprocess_text(desc)
index = row['entity_id']
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
return output_list
def create_dataset():
# train
# data_path = '../../../esAppMod_data_import/test.csv'
data_path = '../../../esAppMod_data_import/parent_test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
# combined_data = DatasetDict({
# 'train': Dataset.from_list(process_df_to_dict(train_df)),
# })
return Dataset.from_list(process_df_to_dict(test_df))
# %%
def test():
test_dataset = create_dataset()
# prepare tokenizer
checkpoint_directory = f'../checkpoint'
# Use glob to find matching paths
# path is usually checkpoint_fold_1/checkpoint-<step number>
# we are guaranteed to save only 1 checkpoint from training
pattern = 'checkpoint_part1-*'
model_checkpoint = glob.glob(os.path.join(checkpoint_directory, pattern))[0]
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, return_tensors="pt", clean_up_tokenization_spaces=True)
# Define additional special tokens
# additional_special_tokens = ["<THING_START>", "<THING_END>", "<PROPERTY_START>", "<PROPERTY_END>", "<NAME>", "<DESC>", "<SIG>", "<UNIT>", "<DATA_TYPE>"]
# Add the additional special tokens to the tokenizer
# tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
# %%
# compute max token length
max_length = 0
for sample in test_dataset['text']:
# Tokenize the sample and get the length
input_ids = tokenizer(sample, truncation=False, add_special_tokens=True)["input_ids"]
length = len(input_ids)
# Update max_length if this sample is longer
if length > max_length:
max_length = length
print(max_length)
# %%
max_length = 128
# given a dataset entry, run it through the tokenizer
def preprocess_function(example):
input = example['text']
# text_target sets the corresponding label to inputs
# there is no need to create a separate 'labels'
model_inputs = tokenizer(
input,
max_length=max_length,
# truncation=True,
padding='max_length'
)
return model_inputs
# map maps function to each "row" in the dataset
# aka the data in the immediate nesting
datasets = test_dataset.map(
preprocess_function,
batched=True,
num_proc=8,
remove_columns="text",
)
datasets.set_format(type='torch', columns=['input_ids', 'attention_mask', 'label'])
# %% temp
# tokenized_datasets['train'].rename_columns()
# %%
# create data collator
# data_collator = DataCollatorWithPadding(tokenizer=tokenizer, padding="max_length")
# %%
# compute metrics
# metric = evaluate.load("accuracy")
#
#
# def compute_metrics(eval_preds):
# preds, labels = eval_preds
# preds = np.argmax(preds, axis=1)
# return metric.compute(predictions=preds, references=labels)
model = AutoModelForSequenceClassification.from_pretrained(
model_checkpoint,
num_labels=len(target_id_list),
id2label=id2label,
label2id=label2id)
# important! after extending tokens vocab
model.resize_token_embeddings(len(tokenizer))
model = model.eval()
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model.to(device)
pred_labels = []
actual_labels = []
dataloader = DataLoader(datasets, batch_size=BATCH_SIZE, shuffle=False)
for batch in tqdm(dataloader):
# Inference in batches
input_ids = batch['input_ids']
attention_mask = batch['attention_mask']
# save labels too
actual_labels.extend(batch['label'])
# Move to GPU if available
input_ids = input_ids.to(device)
attention_mask = attention_mask.to(device)
# Perform inference
with torch.no_grad():
logits = model(
input_ids,
attention_mask).logits
predicted_class_ids = logits.argmax(dim=1).to("cpu")
pred_labels.extend(predicted_class_ids)
pred_labels = [tensor.item() for tensor in pred_labels]
# %%
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, confusion_matrix
y_true = actual_labels
y_pred = pred_labels
# Compute metrics
accuracy = accuracy_score(y_true, y_pred)
average_parameter = 'weighted'
zero_division_parameter = 0
f1 = f1_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
precision = precision_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
recall = recall_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
with open("output_1.txt", "a") as f:
print('*' * 80, file=f)
# Print the results
print(f'Accuracy: {accuracy:.5f}', file=f)
print(f'F1 Score: {f1:.5f}', file=f)
print(f'Precision: {precision:.5f}', file=f)
print(f'Recall: {recall:.5f}', file=f)
# export result
label_list = [id2label[id] for id in pred_labels]
df = pd.DataFrame({
'class_prediction': pd.Series(label_list)
})
# we can save the t5 generation output here
df.to_csv(f"exports/result_1.csv", index=False)
# %%
# reset file before writing to it
with open("output_1.txt", "w") as f:
print('', file=f)
test()

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# %%
# from datasets import load_from_disk
import os
import glob
os.environ['NCCL_P2P_DISABLE'] = '1'
os.environ['NCCL_IB_DISABLE'] = '1'
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
import re
import torch
from torch.utils.data import DataLoader
from transformers import (
AutoTokenizer,
AutoModelForSequenceClassification,
DataCollatorWithPadding,
)
import evaluate
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
from datasets import Dataset, DatasetDict
from tqdm import tqdm
torch.set_float32_matmul_precision('high')
BATCH_SIZE = 256
# %%
# construct the target id list
# data_path = '../../../esAppMod_data_import/train.csv'
data_path = '../../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# rather than use pattern, we use the real thing and property
entity_ids = train_df['entity_id'].to_list()
target_id_list = sorted(list(set(entity_ids)))
# %%
id2label = {}
label2id = {}
for idx, val in enumerate(target_id_list):
id2label[idx] = val
label2id[val] = idx
# introduce pre-processing functions
def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Substitute digits with '#'
text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()
return text
# outputs a list of dictionaries
# processes dataframe into lists of dictionaries
# each element maps input to output
# input: tag_description
# output: class label
def process_df_to_dict(df):
output_list = []
for _, row in df.iterrows():
desc = row['mention']
desc = preprocess_text(desc)
index = row['entity_id']
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
return output_list
def create_dataset():
# train
# data_path = '../../../esAppMod_data_import/test.csv'
data_path = '../../../esAppMod_data_import/test.csv'
test_df = pd.read_csv(data_path, skipinitialspace=True)
# combined_data = DatasetDict({
# 'train': Dataset.from_list(process_df_to_dict(train_df)),
# })
return Dataset.from_list(process_df_to_dict(test_df))
# %%
def test():
test_dataset = create_dataset()
# prepare tokenizer
checkpoint_directory = f'../checkpoint'
# Use glob to find matching paths
# path is usually checkpoint_fold_1/checkpoint-<step number>
# we are guaranteed to save only 1 checkpoint from training
pattern = 'checkpoint-*'
model_checkpoint = glob.glob(os.path.join(checkpoint_directory, pattern))[0]
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, return_tensors="pt", clean_up_tokenization_spaces=True)
# Define additional special tokens
# additional_special_tokens = ["<THING_START>", "<THING_END>", "<PROPERTY_START>", "<PROPERTY_END>", "<NAME>", "<DESC>", "<SIG>", "<UNIT>", "<DATA_TYPE>"]
# Add the additional special tokens to the tokenizer
# tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
# %%
# compute max token length
max_length = 0
for sample in test_dataset['text']:
# Tokenize the sample and get the length
input_ids = tokenizer(sample, truncation=False, add_special_tokens=True)["input_ids"]
length = len(input_ids)
# Update max_length if this sample is longer
if length > max_length:
max_length = length
print(max_length)
# %%
max_length = 128
# given a dataset entry, run it through the tokenizer
def preprocess_function(example):
input = example['text']
# text_target sets the corresponding label to inputs
# there is no need to create a separate 'labels'
model_inputs = tokenizer(
input,
max_length=max_length,
# truncation=True,
padding='max_length'
)
return model_inputs
# map maps function to each "row" in the dataset
# aka the data in the immediate nesting
datasets = test_dataset.map(
preprocess_function,
batched=True,
num_proc=8,
remove_columns="text",
)
datasets.set_format(type='torch', columns=['input_ids', 'attention_mask', 'label'])
# %% temp
# tokenized_datasets['train'].rename_columns()
# %%
# create data collator
# data_collator = DataCollatorWithPadding(tokenizer=tokenizer, padding="max_length")
# %%
# compute metrics
# metric = evaluate.load("accuracy")
#
#
# def compute_metrics(eval_preds):
# preds, labels = eval_preds
# preds = np.argmax(preds, axis=1)
# return metric.compute(predictions=preds, references=labels)
model = AutoModelForSequenceClassification.from_pretrained(
model_checkpoint,
num_labels=len(target_id_list),
id2label=id2label,
label2id=label2id)
# important! after extending tokens vocab
model.resize_token_embeddings(len(tokenizer))
model = model.eval()
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model.to(device)
pred_labels = []
actual_labels = []
dataloader = DataLoader(datasets, batch_size=BATCH_SIZE, shuffle=False)
for batch in tqdm(dataloader):
# Inference in batches
input_ids = batch['input_ids']
attention_mask = batch['attention_mask']
# save labels too
actual_labels.extend(batch['label'])
# Move to GPU if available
input_ids = input_ids.to(device)
attention_mask = attention_mask.to(device)
# Perform inference
with torch.no_grad():
logits = model(
input_ids,
attention_mask).logits
predicted_class_ids = logits.argmax(dim=1).to("cpu")
pred_labels.extend(predicted_class_ids)
pred_labels = [tensor.item() for tensor in pred_labels]
# %%
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, confusion_matrix
y_true = actual_labels
y_pred = pred_labels
# Compute metrics
accuracy = accuracy_score(y_true, y_pred)
average_parameter = 'weighted'
zero_division_parameter = 0
f1 = f1_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
precision = precision_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
recall = recall_score(y_true, y_pred, average=average_parameter, zero_division=zero_division_parameter)
with open("output_2.txt", "a") as f:
print('*' * 80, file=f)
# Print the results
print(f'Accuracy: {accuracy:.5f}', file=f)
print(f'F1 Score: {f1:.5f}', file=f)
print(f'Precision: {precision:.5f}', file=f)
print(f'Recall: {recall:.5f}', file=f)
# export result
label_list = [id2label[id] for id in pred_labels]
df = pd.DataFrame({
'class_prediction': pd.Series(label_list)
})
# we can save the t5 generation output here
df.to_csv(f"exports/result_2.csv", index=False)
# %%
# reset file before writing to it
with open("output_2.txt", "w") as f:
print('', file=f)
test()

234
train/class_bert_process/train.py → train/class_bert_hierarchical/train_1.py
View File

@ -45,7 +45,7 @@ def set_seed(seed):
set_seed(42)
SHUFFLES=2
SHUFFLES=5
# %%
@ -56,37 +56,6 @@ train_df = pd.read_csv(data_path, skipinitialspace=True)
entity_ids = train_df['entity_id'].to_list()
target_id_list = sorted(list(set(entity_ids)))
def compute_normalized_class_weights(class_counts, max_resamples=SHUFFLES):
"""
Compute normalized class weights inversely proportional to class counts.
The weights are normalized so that they sum to 1.
Args:
class_counts (array-like): An array or list where each element represents the count of samples for a class.
Returns:
numpy.ndarray: A normalized array of weights for each class.
"""
class_counts = np.array(class_counts)
total_samples = np.sum(class_counts)
class_weights = total_samples / class_counts
# so that highest weight is 1
normalized_weights = class_weights / np.max(class_weights)
# Scale weights such that the highest weight corresponds to `max_resamples`
resample_counts = normalized_weights * max_resamples
# Round resamples to nearest integer
resample_counts = np.round(resample_counts).astype(int)
return resample_counts
# %%
id_counts = train_df['entity_id'].value_counts()
id_weights = compute_normalized_class_weights(id_counts, max_resamples=SHUFFLES)
id_index = id_counts.index
label2weight = {}
for idx, label in enumerate(id_index):
label2weight[label] = id_weights[idx]
# %%
id2label = {}
label2id = {}
@ -101,20 +70,8 @@ def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Remove any non alphanumeric character
# text = re.sub(r'[^\w\s]', ' ', text) # Retains only alphanumeric and spaces
# replace dashes
text = re.sub(r"[-;:]", " ", text)
# Add space between digit followed by a letter
text = re.sub(r"(\d)([A-Z])", r"\1 \2", text)
# Add space between letter followed by a digit
text = re.sub(r"([A-Z])(\d)", r"\1 \2", text)
# Substitute digits with 'x'
text = re.sub(r'\d+', 'x', text)
text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()
@ -165,35 +122,143 @@ def shuffle_text(text, n_shuffles=SHUFFLES):
return all_processed
term_to_abbrev = {
r'job entry system': 'jes',
r'subversion': 'svn',
r'borland database engine': 'bde',
r'business intelligence and reporting tools': 'birt',
r'lan management solution': 'lms',
r'laboratory information management system': 'lims',
r'ibm database 2': 'db/2',
r'integrated development environment': 'ide',
r'software development kit': 'sdk',
r'hp operations orchestration': 'hpoo',
r'hp server automation': 'hpsa',
r'internet information server': 'iis',
r'release 2': 'r2',
r'red hat enterprise linux': 'rhel',
r'oracle enterprise linux': 'oel',
r'websphere application server': 'was',
r'application development facility': 'adf',
r'server analysis services': 'ssas'
acronym_mapping = {
'hpsa': 'hp server automation',
'tam': 'tivoli access manager',
'adf': 'application development facility',
'html': 'hypertext markup language',
'wff': 'microsoft web farm framework',
'jsp': 'javaserver pages',
'bw': 'business works',
'ssrs': 'sql server reporting services',
'cl': 'control language',
'vba': 'visual basic for applications',
'esapi': 'enterprise security api',
'gwt': 'google web toolkit',
'pki': 'perkin elmer informatics',
'rtd': 'oracle realtime decisions',
'jms': 'java message service',
'db': 'database',
'soa': 'service oriented architecture',
'xsl': 'extensible stylesheet language',
'com': 'compopent object model',
'ldap': 'lightweight directory access protocol',
'odm': 'ibm operational decision manager',
'soql': 'salesforce object query language',
'oms': 'order management system',
'cfml': 'coldfusion markup language',
'nas': 'netscape application server',
'sql': 'structured query language',
'bde': 'borland database engine',
'imap': 'internet message access protocol',
'uws': 'ultidev web server',
'birt': 'business intelligence and reporting tools',
'mdw': 'model driven workflow',
'tws': 'tivoli workload scheduler',
'jre': 'java runtime environment',
'wcs': 'websphere commerce suite',
'was': 'websphere application server',
'ssis': 'sql server integration services',
'xhtml': 'extensible hypertext markup language',
'soap': 'simple object access protocol',
'san': 'storage area network',
'elk': 'elastic stack',
'arr': 'application request routing',
'xlst': 'extensible stylesheet language transformations',
'sccm': 'microsoft endpoint configuration manager',
'ejb': 'enterprise java beans',
'css': 'cascading style sheets',
'hpoo': 'hp operations orchestration',
'xml': 'extensible markup language',
'esb': 'enterprise service bus',
'edi': 'electronic data interchange',
'imsva': 'interscan messaging security virtual appliance',
'wtx': 'ibm websphere transformation extender',
'cgi': 'common gateway interface',
'bal': 'ibm basic assembly language',
'issow': 'integrated safe system of work',
'dcl': 'data control language',
'jdom': 'java document object model',
'fim': 'microsoft forefront identity manager',
'npl': 'niakwa programming language',
'wf': 'windows workflow foundation',
'lm': 'etap license manager',
'wts': 'windows terminal server',
'asp': 'active server pages',
'jil': 'job information language',
'mvc': 'model view controller',
'rmi': 'remote method invocation',
'ad': 'active directory',
'owb': 'oracle warehouse builder',
'rest': 'representational state transfer',
'jdk': 'java development kit',
'ids': 'integrated data store',
'bms': 'batch management software',
'vsx': 'vmware solution exchange',
'ssas': 'sql server analysis services',
'atl': 'atlas transformation language',
'ice': 'infobright community edition',
'esql': 'extended structured query language',
'corba': 'common object request broker architecture',
'dpe': 'device provisioning engines',
'rac': 'oracle real application clusters',
'iemt': 'iis easy migration tool',
'mes': 'manufacturing execution system',
'odbc': 'open database connectivity',
'lms': 'lan management solution',
'wcf': 'windows communication foundation',
'nes': 'netscape enterprise server',
'jsf': 'javaserver faces',
'alm': 'application lifecycle management',
'hlasm': 'high level assembler',
'cmod': 'content manager ondemand'}
external_source = {
'vb.net': 'visual basic dot net',
'jes': 'job entry subsystem',
'svn': 'subversion',
'vcs': 'version control system',
'lims': 'laboratory information management system',
'ide': 'integrated development environment',
'sdk': 'software development kit',
'mq': 'message queue',
'ims': 'information management system',
'isa': 'internet security and acceleration',
'vs': 'visual studio',
'esr': 'extended support release',
'ff': 'firefox',
'vb': 'visual basic',
'rhel': 'red hat enterprise linux',
'iis': 'internet information server',
'api': 'application programming interface',
'se': 'standard edition',
'\.net': 'dot net',
'c#': 'c sharp',
'ms': 'microsoft'
}
abbrev_to_term = {rf'\b{value}\b': key for key, value in term_to_abbrev.items()}
# synonyms = {
# 'windows server': 'windows nt',
# 'windows 7': 'windows desktop',
# 'windows 8': 'windows desktop',
# 'windows 10': 'windows desktop'
# }
# add more information
acronym_mapping.update(external_source)
abbrev_to_term = {f'\b{key}\b': value for key, value in acronym_mapping.items()}
term_to_abbrev = {f'\b{value}\b': key for key, value in acronym_mapping.items()}
def replace_terms_with_abbreviations(text):
for input, replacement in term_to_abbrev.items():
text = re.sub(input, replacement, text)
return text
def replace_abbreivations_with_terms(text):
def replace_abbreviations_with_terms(text):
for input, replacement in abbrev_to_term.items():
text = re.sub(input, replacement, text)
return text
@ -218,8 +283,19 @@ def process_df_to_dict(df):
# no_of_shuffles = label2weight[index] + 1
no_of_shuffles = SHUFFLES
processed_descs = shuffle_text(parent_desc, n_shuffles=no_of_shuffles)
for desc in processed_descs:
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# remove all non-alphanumerics
desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
@ -227,24 +303,21 @@ def process_df_to_dict(df):
output_list.append(element)
# augmentation
# perform abbrev_to_term
desc = replace_terms_with_abbreviations(parent_desc)
no_of_shuffles = SHUFFLES
processed_descs = shuffle_text(desc, n_shuffles=no_of_shuffles)
for desc in processed_descs:
temp_desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
desc = replace_terms_with_abbreviations(temp_desc)
if (desc != temp_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# perform term to abbrev
desc = replace_abbreivations_with_terms(parent_desc)
no_of_shuffles = SHUFFLES
processed_descs = shuffle_text(desc, n_shuffles=no_of_shuffles)
for desc in processed_descs:
desc = replace_abbreviations_with_terms(parent_desc)
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
@ -257,7 +330,7 @@ def process_df_to_dict(df):
def create_dataset():
# train
data_path = '../../esAppMod_data_import/train.csv'
data_path = '../../esAppMod_data_import/parent_train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
@ -271,13 +344,13 @@ def create_dataset():
def train():
save_path = f'checkpoint'
save_path = f'checkpoint_part1'
split_datasets = create_dataset()
# prepare tokenizer
model_checkpoint = "distilbert/distilbert-base-uncased"
# model_checkpoint = 'google-bert/bert-base-cased'
# model_checkpoint = 'google-bert/bert-base-uncased'
# model_checkpoint = 'prajjwal1/bert-small'
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, return_tensors="pt", clean_up_tokenization_spaces=True)
# Define additional special tokens
@ -348,7 +421,6 @@ def train():
training_args = TrainingArguments(
output_dir=f"{save_path}",
# eval_strategy="epoch",
eval_strategy="no",
logging_dir="tensorboard-log",
logging_strategy="epoch",

469
train/class_bert_hierarchical/train_2.py Normal file
View File

@ -0,0 +1,469 @@
# %%
# from datasets import load_from_disk
import os
os.environ['NCCL_P2P_DISABLE'] = '1'
os.environ['NCCL_IB_DISABLE'] = '1'
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"] = "0,1,2,3"
import re
import random
import glob
import torch
from transformers import (
AutoTokenizer,
AutoModelForSequenceClassification,
DataCollatorWithPadding,
Trainer,
EarlyStoppingCallback,
TrainingArguments
)
import evaluate
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
from datasets import Dataset, DatasetDict
torch.set_float32_matmul_precision('high')
# %%
def set_seed(seed):
"""
Set the random seed for reproducibility.
"""
random.seed(seed) # Python random module
np.random.seed(seed) # NumPy random
torch.manual_seed(seed) # PyTorch CPU
torch.cuda.manual_seed(seed) # PyTorch GPU
torch.cuda.manual_seed_all(seed) # If using multiple GPUs
torch.backends.cudnn.deterministic = True # Ensure deterministic behavior
torch.backends.cudnn.benchmark = False # Disable optimization for reproducibility
set_seed(42)
SHUFFLES=0
# %%
# import training file
data_path = '../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
# rather than use pattern, we use the real thing and property
entity_ids = train_df['entity_id'].to_list()
target_id_list = sorted(list(set(entity_ids)))
# %%
id2label = {}
label2id = {}
for idx, val in enumerate(target_id_list):
id2label[idx] = val
label2id[val] = idx
# %%
# introduce pre-processing functions
def preprocess_text(text):
# 1. Make all uppercase
text = text.lower()
# Substitute digits with 'x'
text = re.sub(r'\d+', '#', text)
# standardize spacing
text = re.sub(r'\s+', ' ', text).strip()
return text
def generate_random_shuffles(text, n):
"""
Generate n strings with randomly shuffled words from the input text.
Args:
text (str): The input text.
n (int): The number of random variations to generate.
Returns:
list: A list of strings with shuffled words.
"""
words = text.split() # Split the input into words
shuffled_variations = []
for _ in range(n):
shuffled = words[:] # Copy the word list to avoid in-place modification
random.shuffle(shuffled) # Randomly shuffle the words
shuffled_variations.append(" ".join(shuffled)) # Join the words back into a string
return shuffled_variations
# generate n more shuffled examples
def shuffle_text(text, n_shuffles=SHUFFLES):
"""
Preprocess a list of texts and add n random shuffles for each string.
Args:
texts (list): An input strings.
n_shuffles (int): Number of random shuffles to generate for each string.
Returns:
list: A list of preprocessed and shuffled strings.
"""
all_processed = []
all_processed.append(text)
# Generate random shuffles
shuffled_variations = generate_random_shuffles(text, n_shuffles)
all_processed.extend(shuffled_variations)
return all_processed
acronym_mapping = {
'hpsa': 'hp server automation',
'tam': 'tivoli access manager',
'adf': 'application development facility',
'html': 'hypertext markup language',
'wff': 'microsoft web farm framework',
'jsp': 'javaserver pages',
'bw': 'business works',
'ssrs': 'sql server reporting services',
'cl': 'control language',
'vba': 'visual basic for applications',
'esapi': 'enterprise security api',
'gwt': 'google web toolkit',
'pki': 'perkin elmer informatics',
'rtd': 'oracle realtime decisions',
'jms': 'java message service',
'db': 'database',
'soa': 'service oriented architecture',
'xsl': 'extensible stylesheet language',
'com': 'compopent object model',
'ldap': 'lightweight directory access protocol',
'odm': 'ibm operational decision manager',
'soql': 'salesforce object query language',
'oms': 'order management system',
'cfml': 'coldfusion markup language',
'nas': 'netscape application server',
'sql': 'structured query language',
'bde': 'borland database engine',
'imap': 'internet message access protocol',
'uws': 'ultidev web server',
'birt': 'business intelligence and reporting tools',
'mdw': 'model driven workflow',
'tws': 'tivoli workload scheduler',
'jre': 'java runtime environment',
'wcs': 'websphere commerce suite',
'was': 'websphere application server',
'ssis': 'sql server integration services',
'xhtml': 'extensible hypertext markup language',
'soap': 'simple object access protocol',
'san': 'storage area network',
'elk': 'elastic stack',
'arr': 'application request routing',
'xlst': 'extensible stylesheet language transformations',
'sccm': 'microsoft endpoint configuration manager',
'ejb': 'enterprise java beans',
'css': 'cascading style sheets',
'hpoo': 'hp operations orchestration',
'xml': 'extensible markup language',
'esb': 'enterprise service bus',
'edi': 'electronic data interchange',
'imsva': 'interscan messaging security virtual appliance',
'wtx': 'ibm websphere transformation extender',
'cgi': 'common gateway interface',
'bal': 'ibm basic assembly language',
'issow': 'integrated safe system of work',
'dcl': 'data control language',
'jdom': 'java document object model',
'fim': 'microsoft forefront identity manager',
'npl': 'niakwa programming language',
'wf': 'windows workflow foundation',
'lm': 'etap license manager',
'wts': 'windows terminal server',
'asp': 'active server pages',
'jil': 'job information language',
'mvc': 'model view controller',
'rmi': 'remote method invocation',
'ad': 'active directory',
'owb': 'oracle warehouse builder',
'rest': 'representational state transfer',
'jdk': 'java development kit',
'ids': 'integrated data store',
'bms': 'batch management software',
'vsx': 'vmware solution exchange',
'ssas': 'sql server analysis services',
'atl': 'atlas transformation language',
'ice': 'infobright community edition',
'esql': 'extended structured query language',
'corba': 'common object request broker architecture',
'dpe': 'device provisioning engines',
'rac': 'oracle real application clusters',
'iemt': 'iis easy migration tool',
'mes': 'manufacturing execution system',
'odbc': 'open database connectivity',
'lms': 'lan management solution',
'wcf': 'windows communication foundation',
'nes': 'netscape enterprise server',
'jsf': 'javaserver faces',
'alm': 'application lifecycle management',
'hlasm': 'high level assembler',
'cmod': 'content manager ondemand'}
external_source = {
'vb.net': 'visual basic dot net',
'jes': 'job entry subsystem',
'svn': 'subversion',
'vcs': 'version control system',
'lims': 'laboratory information management system',
'ide': 'integrated development environment',
'sdk': 'software development kit',
'mq': 'message queue',
'ims': 'information management system',
'isa': 'internet security and acceleration',
'vs': 'visual studio',
'esr': 'extended support release',
'ff': 'firefox',
'vb': 'visual basic',
'rhel': 'red hat enterprise linux',
'iis': 'internet information server',
'api': 'application programming interface',
'se': 'standard edition',
'\.net': 'dot net',
'c#': 'c sharp',
'ms': 'microsoft'
}
# synonyms = {
# 'windows server': 'windows nt',
# 'windows 7': 'windows desktop',
# 'windows 8': 'windows desktop',
# 'windows 10': 'windows desktop'
# }
# add more information
acronym_mapping.update(external_source)
abbrev_to_term = {f'\b{key}\b': value for key, value in acronym_mapping.items()}
term_to_abbrev = {f'\b{value}\b': key for key, value in acronym_mapping.items()}
def replace_terms_with_abbreviations(text):
for input, replacement in term_to_abbrev.items():
text = re.sub(input, replacement, text)
return text
def replace_abbreviations_with_terms(text):
for input, replacement in abbrev_to_term.items():
text = re.sub(input, replacement, text)
return text
# outputs a list of dictionaries
# processes dataframe into lists of dictionaries
# each element maps input to output
# input: tag_description
# output: class label
def process_df_to_dict(df):
output_list = []
for _, row in df.iterrows():
# produce shuffling
index = row['entity_id']
parent_desc = row['mention']
parent_desc = preprocess_text(parent_desc)
# ensure at least 1 shuffle
# no_of_shuffles = label2weight[index] + 1
no_of_shuffles = SHUFFLES
processed_descs = shuffle_text(parent_desc, n_shuffles=no_of_shuffles)
for desc in processed_descs:
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# remove all non-alphanumerics
desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# perform abbrev_to_term
temp_desc = re.sub(r'[^\w\s]', ' ', parent_desc) # Retains only alphanumeric and spaces
desc = replace_terms_with_abbreviations(temp_desc)
if (desc != temp_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
# augmentation
# perform term to abbrev
desc = replace_abbreviations_with_terms(parent_desc)
if (desc != parent_desc):
element = {
'text' : desc,
'label': label2id[index], # ensure labels starts from 0
}
output_list.append(element)
return output_list
def create_dataset():
# train
data_path = '../../esAppMod_data_import/train.csv'
train_df = pd.read_csv(data_path, skipinitialspace=True)
combined_data = DatasetDict({
'train': Dataset.from_list(process_df_to_dict(train_df)),
})
return combined_data
# %%
def train():
save_path = f'checkpoint'
split_datasets = create_dataset()
# prepare tokenizer
pattern = 'checkpoint_part1-*'
checkpoint_directory = 'checkpoint'
model_checkpoint = glob.glob(os.path.join(checkpoint_directory, pattern))[0]
# model_checkpoint = "distilbert/distilbert-base-uncased"
# model_checkpoint = 'google-bert/bert-base-uncased'
# model_checkpoint = 'prajjwal1/bert-small'
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint, return_tensors="pt", clean_up_tokenization_spaces=True)
# Define additional special tokens
# additional_special_tokens = ["<DESC>"]
# Add the additional special tokens to the tokenizer
# tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens})
max_length = 120
# given a dataset entry, run it through the tokenizer
def preprocess_function(example):
input = example['text']
# text_target sets the corresponding label to inputs
# there is no need to create a separate 'labels'
model_inputs = tokenizer(
input,
max_length=max_length,
truncation=True,
padding=True
)
return model_inputs
# map maps function to each "row" in the dataset
# aka the data in the immediate nesting
tokenized_datasets = split_datasets.map(
preprocess_function,
batched=True,
num_proc=8,
remove_columns="text",
)
# %% temp
# tokenized_datasets['train'].rename_columns()
# %%
# create data collator
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
# %%
# compute metrics
metric = evaluate.load("accuracy")
def compute_metrics(eval_preds):
preds, labels = eval_preds
preds = np.argmax(preds, axis=1)
return metric.compute(predictions=preds, references=labels)
# %%
# create id2label and label2id
# %%
model = AutoModelForSequenceClassification.from_pretrained(
model_checkpoint,
num_labels=len(target_id_list),
id2label=id2label,
label2id=label2id)
# important! after extending tokens vocab
model.resize_token_embeddings(len(tokenizer))
# model = torch.compile(model, backend="inductor", dynamic=True)
# %%
# Trainer
training_args = TrainingArguments(
output_dir=f"{save_path}",
eval_strategy="no",
logging_dir="tensorboard-log",
logging_strategy="epoch",
# save_strategy="epoch",
load_best_model_at_end=False,
learning_rate=5e-5,
per_device_train_batch_size=64,
per_device_eval_batch_size=64,
auto_find_batch_size=False,
ddp_find_unused_parameters=False,
weight_decay=0.01,
save_total_limit=1,
num_train_epochs=300,
warmup_steps=400,
bf16=True,
push_to_hub=False,
remove_unused_columns=False,
)
trainer = Trainer(
model,
training_args,
train_dataset=tokenized_datasets["train"],
tokenizer=tokenizer,
data_collator=data_collator,
compute_metrics=compute_metrics,
# callbacks=[EarlyStoppingCallback(early_stopping_patience=3)],
)
# uncomment to load training from checkpoint
# checkpoint_path = 'default_40_1/checkpoint-5600'
# trainer.train(resume_from_checkpoint=checkpoint_path)
trainer.train()
# execute training
train()
# %%

2
train/seq2seq_t5_simple/mapping_prediction/output.txt
View File

@ -1,2 +0,0 @@
Accuracy for fold: 0.5846658466584665

0
train/seq2seq_t5_simple/mapping_prediction/.gitignore → train/seq2seq_t5_simple/prediction/.gitignore vendored
View File

6
train/seq2seq_t5_simple/mapping_prediction/inference.py → train/seq2seq_t5_simple/prediction/inference.py
View File

@ -57,10 +57,10 @@ class Inference():
output_list = []
for _, row in df.iterrows():
desc = row['mention']
label = row['entity_name']
label = row['entity_seq']
element = {
'input' : desc,
'output': label
'output': f'{label}'
}
output_list.append(element)
@ -101,7 +101,7 @@ class Inference():
def generate(self):
device = torch.device('cuda:1' if torch.cuda.is_available() else 'cpu')
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
MAX_GENERATE_LENGTH = 128
pred_generations = []

2
train/seq2seq_t5_simple/prediction/output.txt Normal file
View File

@ -0,0 +1,2 @@
Accuracy for fold: 0.5022550225502255

13
train/seq2seq_t5_simple/mapping_prediction/predict.py → train/seq2seq_t5_simple/prediction/predict.py
View File

@ -11,7 +11,7 @@ BATCH_SIZE = 512
def infer():
print(f"Inference for data")
# import test data
data_path = '../../../data_import/test.csv'
data_path = '../../../esAppMod_data_import/test_seq.csv'
df = pd.read_csv(data_path, skipinitialspace=True)
@ -35,18 +35,19 @@ def infer():
# thing_actual_list, property_actual_list = decode_preds(pred_labels)
# Convert the list to a Pandas DataFrame
df_out = pd.DataFrame({
'predictions': prediction_list
'class_prediction': prediction_list
})
# df_out['p_thing_correct'] = df_out['p_thing'] == df_out['thing']
# df_out['p_property_correct'] = df_out['p_property'] == df_out['property']
df = pd.concat([df, df_out], axis=1)
# df = pd.concat([df, df_out], axis=1)
# we can save the t5 generation output here
df.to_csv(f"exports/result.csv", index=False)
df_out.to_csv(f"exports/result.csv", index=False)
# here we want to evaluate mapping accuracy within the valid in mdm data only
condition_correct = df['predictions'] == df['entity_name']
pred_correct_proportion = sum(condition_correct)/len(df)
# predictions = pd.to_numeric(df_out['class_prediction'], errors="coerce")
condition_correct = df_out['class_prediction'] == df['entity_seq']
pred_correct_proportion = sum(condition_correct)/len(df_out)
# write output to file output.txt
with open("output.txt", "a") as f:

6
train/seq2seq_t5_simple/train.py
View File

@ -33,10 +33,10 @@ def process_df_to_dict(df):
output_list = []
for _, row in df.iterrows():
desc = row['mention']
label = row['entity_name']
label = row['entity_seq']
element = {
'input' : desc,
'output': label
'output': f'{label}'
}
output_list.append(element)
@ -45,7 +45,7 @@ def process_df_to_dict(df):
def create_dataset():
# train
data_path = f"../../data_import/train.csv"
data_path = f"../../esAppMod_data_import/train_seq.csv"
train_df = pd.read_csv(data_path, skipinitialspace=True)
combined_data = DatasetDict({

11
zero_shot/bloom.py
View File

@ -3,8 +3,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
# %%
# Load model and tokenizer
# model_name = "bigscience/bloom-7b1" # Replace with your model
model_name = "bigscience/bloomz-1b1"
model_name = "bigscience/bloom-7b1" # Replace with your model
# model_name = "bigscience/bloomz-1b1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
# Automatically map model layers to available GPUs
@ -26,13 +26,12 @@ outputs = model.generate(inputs["input_ids"], max_length=50)
# Decode and print result
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
# %%
# %%
# Prepare input
def generate(text):
# Define prompt
prompt = f"Answer Concisely: Give me a mapping between the acronym and descriptor in the format '(acronym: description): '{text}'"
prompt = f"Give me past product names relating to: '{text}'"
# Generate acronym
inputs = tokenizer(prompt, return_tensors="pt")
@ -45,7 +44,7 @@ def generate(text):
# Example usage
# text = "Advanced Data Analytics Platform"
text = 'ColdFusion Markup Language (CFML)'
text = 'windows server'
acronym = generate(text)
print(f"Acronym: {acronym}")
print(f"Generation: {acronym}")
# %%

21
zero_shot/conceptnet.py Normal file
View File

@ -0,0 +1,21 @@
# %%
import requests
def get_related_terms(term, language="en", limit=10):
url = f"http://api.conceptnet.io/c/{language}/{term}"
response = requests.get(url).json()
# Extract related terms
related_terms = []
for edge in response.get("edges", []):
related = edge.get("end", {}).get("label", None)
if related and related.lower() != term.lower():
related_terms.append(related)
if len(related_terms) >= limit:
break
return related_terms
# Example
related_terms = get_related_terms("windows_server")
print("Related Terms:", related_terms)
# %%

38
zero_shot/dbpedia.py Normal file
View File

@ -0,0 +1,38 @@
# %%
from SPARQLWrapper import SPARQLWrapper, JSON
# %%
sparql = SPARQLWrapper("https://dbpedia.org/sparql")
sparql.setQuery("""
SELECT ?altLabel WHERE {
?item rdfs:label "Windows Server"@en.
?item skos:altLabel ?altLabel.
FILTER (LANG(?altLabel) = "en")
}
LIMIT 10
""")
sparql.setReturnFormat(JSON)
results = sparql.query().convert()
for result in results["results"]["bindings"]:
print(result["label"]["value"])
# %%
from SPARQLWrapper import SPARQLWrapper, JSON
sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
sparql.setQuery("""
SELECT ?itemLabel ?altLabel WHERE {
?item ?label "Windows Server"@en.
OPTIONAL { ?item skos:altLabel ?altLabel. FILTER (LANG(?altLabel) = "en") }
SERVICE wikibase:label { bd:serviceParam wikibase:language "en". }
}
LIMIT 10
""")
sparql.setReturnFormat(JSON)
results = sparql.query().convert()
for result in results["results"]["bindings"]:
print("Label:", result["itemLabel"]["value"])
if "altLabel" in result:
print("Alias:", result["altLabel"]["value"])
# %%

626
zero_shot/error.csv Normal file
View File

@ -0,0 +1,626 @@
,mention,entity_id,entity_name,class_prediction,predicted_name
0,DOT NET,497,.NET Framework,579,Unix|BSD|*
2,Dot net - FW 4,497,.NET Framework,368,VB.NET
3,.Net 4.7.1 Enterprise Lib,497,.NET Framework,368,VB.NET
11,.NET,497,.NET Framework,579,Unix|BSD|*
13,.Net 4.5.2 Enterprise Lib,497,.NET Framework,368,VB.NET
40,APACHE LOG4NET,483,.NET Framework|log4net,394,Java|Log4j
41,LOG4NET,483,.NET Framework|log4net,394,Java|Log4j
42,Magik,484,.NET Framework|Magick.NET,533,YAML
43,WCF,485,.NET Framework|Windows Communication Foundation (WCF),486,.NET Framework|Windows Workflow Foundation (WF)
45,WWF,486,.NET Framework|Windows Workflow Foundation (WF),443,OS/2
47,Ejes,1,(E)JES,101,Microsoft Dynamics AX
48,(UNIRITA) A-AUTO 7.2.2,2,A-Auto Job Scheduling Software,299,AutoIt
50,Active Directoy,498,Active Directory (AD),40,Connect Direct
54,APSX,592,Active Server Pages (ASP)|*,609,IIS|*
69,Andriod,418,Android,586,PHP|*
71,Apache Active Queue,6,Apache ActiveMQ,259,Apache HTTP Server
72,MQ Apache Active Queue,6,Apache ActiveMQ,81,IBM Websphere MQ
75,cordova-android,501,Apache Cordova,418,Android
77,Hive,8,Apache Hive,177,SAP NetWeaver Business Warehouse
99,solr,11,Apache Solr,375,Apache Lucene
135,ADF,13,Application Development Facility (ADF),130,Oracle ADF
144,WLS 10.2,600,Oracle WebLogic Server|*,442,OpenVMS
149,BEA WLS,600,Oracle WebLogic Server|*,442,OpenVMS
152,Weblogic 12c,600,Oracle WebLogic Server|*,582,C#|*
160,WLE,600,Oracle WebLogic Server|*,443,OS/2
168,Web Logic,600,Oracle WebLogic Server|*,97,MarkLogic DB
174,BEA WLE,600,Oracle WebLogic Server|*,443,OS/2
175,WLS 10,600,Oracle WebLogic Server|*,442,OpenVMS
176,WLS,600,Oracle WebLogic Server|*,442,OpenVMS
189,brain script,302,Brainscript,369,VBScript
190,BRAINScript,302,Brainscript,367,TypeScript
191,Business Intelligence and Reporting Tools,21,Business Intelligence and Reporting Tools (BIRT),133,Oracle Business Intelligence
192,Actuate Report Server,21,Business Intelligence and Reporting Tools (BIRT),42,Crystal Reports
194,CSHARP,582,C#|*,87,Informatica PowerCenter
218,WinFrame,30,Citrix Virtual Apps and Desktops,443,OS/2
221,METAFRAME,30,Citrix Virtual Apps and Desktops,406,JavaScript|AngularJS
225,Presentation Server,30,Citrix Virtual Apps and Desktops,541,File Server
226,NETSCALER-1.5,563,Citrix ADC,273,Netscape Enterprise Server (NES)
227,NETSCALER-11.,563,Citrix ADC,273,Netscape Enterprise Server (NES)
228,Citrix SD-WAN,563,Citrix ADC,30,Citrix Virtual Apps and Desktops
229,NetScaler SD-WAN,563,Citrix ADC,273,Netscape Enterprise Server (NES)
231,NetScaler ADC,563,Citrix ADC,272,Netscape Application Server (NAS)
236,NetScaler SDX,291,Citrix ADC SDX,273,Netscape Enterprise Server (NES)
240,Provisioning Services 7.15.8,32,Citrix Provisioning,538,Device Provisioning Engines (DPE)
241,Citrix PVS,32,Citrix Provisioning,30,Citrix Virtual Apps and Desktops
243,CLISTS,309,CLIST,329,IBM i Control Language (CL)
253,CFML,311,ColdFusion Markup Language (CFML),316,eXtensible HyperText Markup Language (XHTML)
254,ColdFusion Markup Language,311,ColdFusion Markup Language (CFML),37,Coldfusion
255,Sterling Connect,40,Connect Direct,542,General Ledger
264,Cormerstone,41,Cornerstone software,516,Compopent Object Model (COM)
265,Cornerstone,41,Cornerstone software,370,Visual Basic
279,DB2 UDB,43,DB2,517,Common Object Request Broker Architecture (CORBA)
282,DB2-UDB,43,DB2,365,TCL
291,DB2/UDB,43,DB2,365,TCL
292,IBM DB2 ENTERPRISE SERVER EDITION PVU OPTION 10.5,43,DB2,163,PVCS Version Manager
300,IBM - IBM DB2 Advanced Enterprise Server Edition PVU Option 10.5,43,DB2,72,IBM Mobile Foundation
301,UDB,43,DB2,517,Common Object Request Broker Architecture (CORBA)
302,IBM - IBM DB2 Enterprise Server Edition Product Trial 9.7,43,DB2,610,Oracle Application Server|*
306,IBM - IBM DB2 Workgroup Server Edition Product Trial 9.7,43,DB2,610,Oracle Application Server|*
313,EZTriev,314,Easytrieve,296,Intel Xeon Processor
314,Eztrieve,314,Easytrieve,296,Intel Xeon Processor
321,PrestoSoft - ExamDiff Application 1.6,49,ExamDiff,346,Pascal|Object Pascal
322,PrestoSoft - ExamDiff Application,49,ExamDiff,346,Pascal|Object Pascal
323,ExamDiff Application,49,ExamDiff,467,MS SQL Server|Log Reader Agent
324,Expect Scripts,315,Expect,109,Microsoft MQ
329,Microsoft - MSXML 4.0 SP2 4.2,318,Extensible Markup Language (XML)|MSXML,316,eXtensible HyperText Markup Language (XHTML)
331,XSL,319,Extensible Stylesheet Language (XSL),320,Extensible Stylesheet Language Transformations (XLST)
332,JAVA-XSL,319,Extensible Stylesheet Language (XSL),320,Extensible Stylesheet Language Transformations (XLST)
335,ServerCA Access GatewayF5,50,F5 Secure Web Gateway Services,290,CA API Gateway
347,HP C++,58,HP aC++ compiler,59,HP C/ANSI C compiler
350,HP C++ 10.20,58,HP aC++ compiler,59,HP C/ANSI C compiler
351,HPC 11.11,59,HP C/ANSI C compiler,58,HP aC++ compiler
358,HFS,505,HTTP File Server,486,.NET Framework|Windows Workflow Foundation (WF)
359,www.rejetto.com - HttpFileServer 2.3,505,HTTP File Server,55,Google Chrome
360,HttpFileServer,505,HTTP File Server,522,Application Web Server
367,IBM - IBM BigFix Platform Client Deploy Tool 9.5,457,IBM BigFix Platform|Client Deploy Tool,62,IBM BigFix Platform
369,IBM BPM,64,IBM Business Process Manager,328,IBM High Level Assembler (HLASM)
375,Data Power,294,IBM DataPower Gateway,295,IBM Power Systems
376,IDG.7.5.2.19hp,294,IBM DataPower Gateway,449,Unix|HP-UX
380,hlasm,328,IBM High Level Assembler (HLASM),438,macOS
383,IHS,265,IBM HTTP Server,424,IBM i
386,WebSphere and IHS,265,IBM HTTP Server,67,IBM InfoSphere DataStage
387,WebSphere http,265,IBM HTTP Server,284,Websphere Application Server (WAS)
391,IBM Websphere HTTP Server,265,IBM HTTP Server,285,WebSphere Liberty
393,WebSphere IHS,265,IBM HTTP Server,601,Websphere ILOG JRules BRMS
394,WebSphere -IHS,265,IBM HTTP Server,601,Websphere ILOG JRules BRMS
397,OS400 V7R1,424,IBM i,443,OS/2
398,OS400,424,IBM i,443,OS/2
399,OS/400,424,IBM i,443,OS/2
408,IIB,68,IBM Integration Bus,370,Visual Basic
411,Extended Structured Query Language,458,IBM Integration Bus|Extended Structured Query Language (ESQL),572,Structured Query Language (SQL)
415,IBM WorkLight,72,IBM Mobile Foundation,649,IBM Cloud
417,ILOG JRules,73,IBM Operational Decision Manager (ODM),601,Websphere ILOG JRules BRMS
420,Decision Center 8.0.1.0,73,IBM Operational Decision Manager (ODM),252,IBM ILOG Views
423,AS400,295,IBM Power Systems,443,OS/2
424,AS/400,295,IBM Power Systems,443,OS/2
426,System i,295,IBM Power Systems,424,IBM i
427,P-series,295,IBM Power Systems,81,IBM Websphere MQ
428,IBM iSeries/AS400 system Model 520,295,IBM Power Systems,443,OS/2
439,Tivoli Asset Discovery for Distributed,459,IBM Tivoli Asset Management|Asset Discovery for Distributed,606,IBM Tivoli Asset Management|*
447,Database MS SQL Agent,77,IBM Tivoli Monitoring,469,MS SQL Server|SQL Server Database Engine
448,Linux OS Agent,77,IBM Tivoli Monitoring,576,Linux|*
449,Database DB2 Agent,77,IBM Tivoli Monitoring,520,Database (DB)
452,Windows OS Agent,77,IBM Tivoli Monitoring,580,Windows|*
454,IBM - IBM TSM FCM,604,IBM Tivoli Storage Manager|*,460,IBM Tivoli Storage Manager|TSM API
459,Databases Data Protection for Microsoft SQL,604,IBM Tivoli Storage Manager|*,572,Structured Query Language (SQL)
461,IBM - IBM Spectrum Protect Data Protection for Microsoft SQL Server 8.1,604,IBM Tivoli Storage Manager|*,469,MS SQL Server|SQL Server Database Engine
462,IBM Spectrum Protect Data Protection,604,IBM Tivoli Storage Manager|*,312,Data Language Interface (DL/I)
463,IBM - IBM Spectrum Protect API 7.1,460,IBM Tivoli Storage Manager|TSM API,294,IBM DataPower Gateway
464,IBM - IBM Spectrum Protect Client,461,IBM Tivoli Storage Manager|TSM Client,294,IBM DataPower Gateway
465,IBM - IBM Tivoli Storage Manager Client,461,IBM Tivoli Storage Manager|TSM Client,604,IBM Tivoli Storage Manager|*
467,VSS Requestor configured 8.1,463,IBM Tivoli Storage Manager|VSS Requestor,577,MVS|*
468,VSS Requestor 7.1,463,IBM Tivoli Storage Manager|VSS Requestor,577,MVS|*
469,TWS-WS,79,IBM Tivoli Workload Scheduler (TWS),239,Windows Terminal Server (WTS)
472,wbia 2.6,80,IBM WebSphere Business Integration Adaptor,627,XtraDB
473,IBM WBIA 2.6.0.12,80,IBM WebSphere Business Integration Adaptor,424,IBM i
475,MQ,81,IBM Websphere MQ,248,ZeroMQ
476,MQ 9.1,81,IBM Websphere MQ,248,ZeroMQ
479,MQ 7,81,IBM Websphere MQ,248,ZeroMQ
480,MQ 6,81,IBM Websphere MQ,248,ZeroMQ
481,MQ 9.0,81,IBM Websphere MQ,248,ZeroMQ
482,MQ 5.3,81,IBM Websphere MQ,248,ZeroMQ
483,MQ 7.01,81,IBM Websphere MQ,248,ZeroMQ
484,MQ 7.5,81,IBM Websphere MQ,248,ZeroMQ
485,MQSeries 8.0,81,IBM Websphere MQ,248,ZeroMQ
488,WSMQ 8.0,81,IBM Websphere MQ,248,ZeroMQ
489,MQ 9.0.5,81,IBM Websphere MQ,248,ZeroMQ
491,WTX,83,IBM WebSphere Transformation Extender (WTX),274,Nginx
505,Microsoft Internet Inf,609,IIS|*,130,Oracle ADF
508,Microsoft Internet Informat,609,IIS|*,330,IBM Informix-4GL
550,Microsoft - IIS 6.0 Migration Tool 1,489,IIS|Easy Migration Tool (IEMT),609,IIS|*
558,Infozip 6,85,Info-ZIP,677,Git
559,Infozip,85,Info-ZIP,677,Git
578,IMSVA 9.1,566,InterScan Messaging Security Virtual Appliance (IMSVA),84,IMS DB
580,IMSVA,566,InterScan Messaging Security Virtual Appliance (IMSVA),84,IMS DB
581,Java 1.8,584,Java|*,334,Java|Java Standard Edition (Java SE)
582,Java 7,584,Java|*,334,Java|Java Standard Edition (Java SE)
583,Java on Weblogic server,584,Java|*,600,Oracle WebLogic Server|*
584,Java5,584,Java|*,334,Java|Java Standard Edition (Java SE)
585,Java 6,584,Java|*,334,Java|Java Standard Edition (Java SE)
586,Java 6.0,584,Java|*,334,Java|Java Standard Edition (Java SE)
587,Java 7 Update 25,584,Java|*,334,Java|Java Standard Edition (Java SE)
589,Java (open source),584,Java|*,397,Java|Servlet
590,Java 5,584,Java|*,334,Java|Java Standard Edition (Java SE)
591,Java 1.5,584,Java|*,334,Java|Java Standard Edition (Java SE)
593,Java 1.8.0_92,584,Java|*,334,Java|Java Standard Edition (Java SE)
594,Java 1.6,584,Java|*,334,Java|Java Standard Edition (Java SE)
595,J2EE 6,584,Java|*,333,Java|Java Enterprise Edition (Java EE)
596,Java (J2EE),584,Java|*,333,Java|Java Enterprise Edition (Java EE)
598,JRE,506,Java Runtime Environment (JRE),84,IMS DB
629,JEE,333,Java|Java Enterprise Edition (Java EE),1,(E)JES
639,JSF,391,Java|JavaServer Faces (JSF),334,Java|Java Standard Edition (Java SE)
643,JSP Scriptlets,336,Java|JavaServer Pages (JSP)|Scriptlets,335,Java|JavaServer Pages (JSP)
644,Java Scriplet,336,Java|JavaServer Pages (JSP)|Scriptlets,88,Ingres
645,Core 9.2.0.0,393,Java|JRuby Core,583,C++|*
647,Java RMI,396,Java|Remote Method Invocation (RMI),584,Java|*
650,Java Servlets,397,Java|Servlet,453,Linux|Fedora
651,Java 6 Servlets,397,Java|Servlet,453,Linux|Fedora
652,J2EE Servlets,397,Java|Servlet,443,OS/2
653,Servlets,397,Java|Servlet,420,Cisco IOS
654,Servlets v2.3,397,Java|Servlet,370,Visual Basic
656,Spring BOOT,399,Java|Spring|Spring Boot,398,Java|Spring
657,Springboot,399,Java|Spring|Spring Boot,398,Java|Spring
661,javasript,589,JavaScript|*,335,Java|JavaServer Pages (JSP)
662,JS,589,JavaScript|*,507,Node.js
664,Java Script,589,JavaScript|*,584,Java|*
671,Sencha 4.2.0,409,JavaScript|Ext JS,589,JavaScript|*
674,jqueryui,412,JavaScript|Jquery|jQuery UI,411,JavaScript|JQuery
675,jquery-ui,412,JavaScript|Jquery|jQuery UI,411,JavaScript|JQuery
679,Scriptaculous,414,JavaScript|script.aculo.us,582,C#|*
684,EAP,268,JBoss|*,174,SAP ERP
685,JBOSS-EAP,268,JBoss|*,493,JBoss|Wildfly
686,JBoss Application Server 4,268,JBoss|*,493,JBoss|Wildfly
687,JBoss Application Server 7,268,JBoss|*,493,JBoss|Wildfly
688,JBoss Application Server 5,268,JBoss|*,493,JBoss|Wildfly
689,JBoss Application Server,268,JBoss|*,493,JBoss|Wildfly
690,Enterprise Application Platform,268,JBoss|*,670,EAServer
692,JBOSS 5.1.2 EAP,268,JBoss|*,493,JBoss|Wildfly
693,server: Jboss,268,JBoss|*,493,JBoss|Wildfly
694,JBOSS 6.3.2 EAP,268,JBoss|*,493,JBoss|Wildfly
695,JBoss EAP 4.3,268,JBoss|*,493,JBoss|Wildfly
700,Job Information Language,339,Job Information Language (JIL),338,JCL
703,JoinIT by Acayosoft,91,joinIT,4,Adobe Acrobat Reader
704,Acayosoft JoinIT,91,joinIT,4,Adobe Acrobat Reader
705,JoinIT by Acayosoft v 9.0.8,91,joinIT,4,Adobe Acrobat Reader
706,LifeFlow Tool,92,LifeFlow,486,.NET Framework|Windows Workflow Foundation (WF)
707,Linux 2.6.32-696.28.1.el6.x86_64,576,Linux|*,437,Linux|zLinux
709,Linux 2.6.32-696.30.1.el6.x86_64,576,Linux|*,437,Linux|zLinux
710,Linux 2.6.9,576,Linux|*,437,Linux|zLinux
711,Linux 2.6.32-642.3.1.el6.x86_64,576,Linux|*,437,Linux|zLinux
712,Linux - 2.6.18-371.1.2.el5,576,Linux|*,437,Linux|zLinux
713,Linux 2.6.32-696.23.1.el6.x86_64,576,Linux|*,437,Linux|zLinux
749,Gaia Kernel version 2.7,428,Linux|Check Point,432,Linux|Oracle Linux
752,Gaia Kernel version 2.6,428,Linux|Check Point,432,Linux|Oracle Linux
766,OEL,432,Linux|Oracle Linux,449,Unix|HP-UX
778,Oracle Enterprise Server 7.5,432,Linux|Oracle Linux,134,Oracle Database
780,OEL6.7 - 3.8.13-68.3.4.el6uek.x86_64,432,Linux|Oracle Linux,449,Unix|HP-UX
792,VMware Photon,433,Linux|Photon OS,569,VMware Server
793,VMware Photon 1,433,Linux|Photon OS,569,VMware Server
809,Red Hat(Linux),434,Linux|Red Hat Enterprise Linux,268,JBoss|*
818,Redhat - Redhat Linux 7.2,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
819,Linux RH6,434,Linux|Red Hat Enterprise Linux,437,Linux|zLinux
865,Redhat - Redhat Linux 6.6,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
870,Redhat - RHEL 7.2,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
874,Red Hat Entreprise Linux 6.2,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
882,Redhat 6 64-Bit,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
893,RED HAT ADVANCED SERVER 5,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
910,redhat6.6,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
912,Redhat - Redhat Linux 6.3,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
913,Linux RH,434,Linux|Red Hat Enterprise Linux,437,Linux|zLinux
916,Redhat - Red Hat(Linux),434,Linux|Red Hat Enterprise Linux,268,JBoss|*
920,Linux RH7,434,Linux|Red Hat Enterprise Linux,437,Linux|zLinux
926,Red Hat V6,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
932,Linux RH5,434,Linux|Red Hat Enterprise Linux,437,Linux|zLinux
934,rehl5.9,434,Linux|Red Hat Enterprise Linux,43,DB2
964,Red Hat 6.6,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
979,red hat,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
991,Redhat,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
996,RedHat 7.3,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
998,LINUX RED HAT 5 EL,434,Linux|Red Hat Enterprise Linux,268,JBoss|*
1003,SUSE11,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1006,Linux SuSE12,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1011,SUSE10,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1012,SUSE Linux 12,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1017,SUSELinux Enterprise 11.x,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1023,SUSE Linux 11,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1024,SUSE Linux 11 SP3,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1029,Linux SuSE11,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1030,SUSE,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1038,SuseLinux,435,Linux|SUSE Linux Enterprise Server,431,Linux|openSUSE
1051,domino8.5,270,Lotus Domino,93,Lotus Notes
1052,Domino 8.x,270,Lotus Domino,93,Lotus Notes
1054,Lucee 5.2.6.60,271,Lucee,375,Apache Lucene
1056,Darwin,438,macOS,117,Mozilla Firefox
1061,Memcache,98,Memcached,18,BMC Control-M
1062,ACCDB,99,Microsoft Access,525,Open Database Connectivity (ODBC)
1070,ConfigMgr,102,Microsoft Endpoint Configuration Manager (SCCM),21,Business Intelligence and Reporting Tools (BIRT)
1080,FIM SQL Development Server,105,Microsoft Forefront Identity Manager (FIM),572,Structured Query Language (SQL)
1082,Microsoft - Internet Explor,107,Microsoft Internet Explorer,356,Rexx
1084,Internet Explor,107,Microsoft Internet Explorer,356,Rexx
1090,SCEP for Linux,110,Microsoft System Center Endpoint Protection,437,Linux|zLinux
1094,SCEP for Mac,110,Microsoft System Center Endpoint Protection,438,macOS
1101,msdeploy,112,Microsoft Web Deploy,56,Greenplum DB
1106,WebPI,114,Microsoft Web Platform Installer,522,Application Web Server
1109,Web PI,114,Microsoft Web Platform Installer,531,Simple Object Access Protocol (SOAP)
1111,MDW Framework,115,Model Driven Workflow (MDW),406,JavaScript|AngularJS
1115,Mango DB,116,MongoDB,43,DB2
1117,MangoDB,116,MongoDB,43,DB2
1125,O365,119,MS Office 365,424,IBM i
1141,MICROSOFT SQL SERVER 2012 DEVELOPER EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1153,MICROSOFT SQL SERVER 2012 STANDARD EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1154,MS SQL Server 2008 Developer,581,MS SQL Server|*,146,Oracle SQL Developer
1156,MICROSOFT SQL SERVER 2008 DEVELOPER EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1167,MSSQL Database Server,581,MS SQL Server|*,122,MySQL
1173,MSSQL2008,581,MS SQL Server|*,122,MySQL
1192,Microsoft SQL Server Standard Edition,581,MS SQL Server|*,121,MS SQL Server Compact
1201,SQLServer,581,MS SQL Server|*,572,Structured Query Language (SQL)
1226,MICROSOFT SQL SERVER 2012 ENTERPRISE EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1233,MICROSOFT SQL SERVER 2005 ENTERPRISE EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1234,SQLSVR2008,581,MS SQL Server|*,352,PL/SQL
1235,MICROSOFT SQL SERVER 2008 ENTERPRISE EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1239,MICROSOFT SQL SERVER 2008 STANDARD EDITION,581,MS SQL Server|*,121,MS SQL Server Compact
1244,MS SQL Server 2012 Developer,581,MS SQL Server|*,146,Oracle SQL Developer
1253,Microsoft - SQL Server Express LocalDB 2014,581,MS SQL Server|*,469,MS SQL Server|SQL Server Database Engine
1256,MSSQL,581,MS SQL Server|*,122,MySQL
1280,Microsoft - Microsoft SQL Server Analysis Services 2012 for Microsoft SQL Server 2012 Standard Edition 2012,468,MS SQL Server|SQL Server Analysis Services (SSAS),581,MS SQL Server|*
1281,Microsoft - Microsoft SQL Server Analysis Services 2014 for Microsoft SQL Server 2014 Standard Edition 2014,468,MS SQL Server|SQL Server Analysis Services (SSAS),581,MS SQL Server|*
1283,Microsoft - Microsoft SQL Server Analysis Services 2014 for Microsoft SQL Server 2014 Enterprise Edition 2014,468,MS SQL Server|SQL Server Analysis Services (SSAS),581,MS SQL Server|*
1290,Microsoft - Microsoft SQL Server Integration Services 2014 for Microsoft SQL Server 2014 Enterprise Edition 2014,470,MS SQL Server|SQL Server Integration Services (SSIS),581,MS SQL Server|*
1293,Microsoft - Microsoft SQL Server Integration Services 2014 for Microsoft SQL Server 2014 Standard Edition 2014,470,MS SQL Server|SQL Server Integration Services (SSIS),581,MS SQL Server|*
1295,SQL Server Integration Services,470,MS SQL Server|SQL Server Integration Services (SSIS),473,MS SQL Server|SQL Server Reporting Services (SSRS)
1316,ZOS Base 1.12,441,MVS|z/OS,437,Linux|zLinux
1335,NAS,272,Netscape Application Server (NAS),443,OS/2
1337,NES,273,Netscape Enterprise Server (NES),443,OS/2
1349,Node.js 0.10 (Linux),507,Node.js,437,Linux|zLinux
1361,Node.js 4 (Linux),507,Node.js,437,Linux|zLinux
1371,Symas OpenLDAP,126,OpenLDAP,178,SAP SQL Anywhere
1377,OAM 12c,129,Oracle Access Management,303,C
1378,ADF 12c,130,Oracle ADF,343,Objective C
1381,OHS,610,Oracle Application Server|*,122,MySQL
1383,Oracle HTTP Server powered by Apache,610,Oracle Application Server|*,259,Apache HTTP Server
1384,j2eeoracleca,610,Oracle Application Server|*,453,Linux|Fedora
1385,Oracle HTTP,610,Oracle Application Server|*,134,Oracle Database
1389,9i AS server,610,Oracle Application Server|*,227,Virtual I/O Server
1391,Oracle Application R12.1.3,610,Oracle Application Server|*,134,Oracle Database
1394,Weblogic BI Publisher,132,Oracle BI Publisher,600,Oracle WebLogic Server|*
1396,OBI,133,Oracle Business Intelligence,343,Objective C
1397,OBIEE,133,Oracle Business Intelligence,343,Objective C
1398,OBI Reporting,133,Oracle Business Intelligence,343,Objective C
1401,Oracle 12.2 Client,134,Oracle Database,610,Oracle Application Server|*
1406,Oracle Database 11g Enterprise Edition Release 11.2.0.4.0,134,Oracle Database,610,Oracle Application Server|*
1407,Oracle 11.2 (Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit) RAC,134,Oracle Database,610,Oracle Application Server|*
1415,Oracle 11 on AIX,134,Oracle Database,445,Unix|AIX
1416,Oracle Database 10g Enterprise Edition Release 10.1.0.4.0 - 64bit,134,Oracle Database,610,Oracle Application Server|*
1431,Oracle Database 10g Release 10.2.0.4.0 - 64bit Production,134,Oracle Database,298,Oracle Exadata
1432,Oarcle 11G,134,Oracle Database,218,TIBCO InConcert
1443,DB - Oracle inbuilt,134,Oracle Database,158,Powerbuilder
1460,Oracle Server,134,Oracle Database,610,Oracle Application Server|*
1475,Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 - 64bit Production,134,Oracle Database,610,Oracle Application Server|*
1480,Oracle 12C on linux,134,Oracle Database,303,C
1484,Oracle9i Enterprise Edition Release 9.2.0.5.0,134,Oracle Database,610,Oracle Application Server|*
1486,Oracle 11g on linux,134,Oracle Database,432,Linux|Oracle Linux
1487,Oracle 11gEssbase,134,Oracle Database,298,Oracle Exadata
1490,JServer Release 9.2.0.5.0,474,Oracle Database|Jserver,335,Java|JavaServer Pages (JSP)
1492,Designer 6i,135,Oracle Designer,516,Compopent Object Model (COM)
1493,Enterprise Manager 12.2.1.1,136,Oracle Enterprise Manager,427,Linux|CentOS
1494,Enterprise Manager 12.2.1.2,136,Oracle Enterprise Manager,427,Linux|CentOS
1495,Enterprise Manager 11.1.1.7,136,Oracle Enterprise Manager,427,Linux|CentOS
1501,"Oracle, Nets",140,Oracle Net Services,273,Netscape Enterprise Server (NES)
1502,Oracle RAC,141,Oracle Real Application Clusters (RAC),134,Oracle Database
1504,ORPOS 13.3.3,142,Oracle Retail Point-of-Service,609,IIS|*
1505,ORPOS 13.3.5,142,Oracle Retail Point-of-Service,609,IIS|*
1506,ORPOS 13.3.4,142,Oracle Retail Point-of-Service,609,IIS|*
1509,OSB Servers,143,Oracle Service Bus,443,OS/2
1514,Oracle TT,147,Oracle TimesTen In-Memory Database,134,Oracle Database
1517,OWB 10g,148,Oracle Warehouse Builder (OWB),300,AWK
1524,Clascal,346,Pascal|Object Pascal,307,Cascading Style Sheets (CSS)
1526,Oracle-HR-9.2,151,PeopleSoft,134,Oracle Database
1529,ActiveState Tool Corp. - ActivePerl 5.12,348,Perl|ActivePerl,500,ActiveX
1530,ActiveState Tool Corp. - ActivePerl 5.8,348,Perl|ActivePerl,500,ActiveX
1531,ORAPERL,417,Perl|Oraperl,242,WinRAR
1532,REX,349,Perl|Rex,356,Rexx
1536,TCServer V6,277,Pivotal tc Server,365,TCL
1537,IBM PKWARE PKZip 2,155,PKZIP,387,Java|IBM SDK
1541,PLQSL,352,PL/SQL,351,PL/I
1542,Oracle - SQL,352,PL/SQL,581,MS SQL Server|*
1544,Oracle SQL,352,PL/SQL,134,Oracle Database
1545,PLSQL;,352,PL/SQL,351,PL/I
1547,Oracle PLSQL,352,PL/SQL,351,PL/I
1548,plsql,352,PL/SQL,351,PL/I
1551,Projectplace,156,Planview,21,Business Intelligence and Reporting Tools (BIRT)
1558,Power Builder,158,Powerbuilder,151,PeopleSoft
1560,Power Builder 6.5,158,Powerbuilder,27,Chef Automate
1565,ProjectWise Oracle Server,161,ProjectWise,162,ProjectWise Web Server
1576,RMQ,165,RabbitMQ,355,R
1579,Clearquest,167,Rational ClearQuest,455,Clarify|Clear Basic
1581,Remedy ARS,169,Remedy,322,Fortran
1584,RightFax client 10,171,RightFax,118,MQ Client
1585,SOQL,359,Salesforce Object Query Language (SOQL),621,ArangoDB
1587,SAP Business Objects,173,SAP BusinessObjects BI server,177,SAP NetWeaver Business Warehouse
1588,Business Objects 12,173,SAP BusinessObjects BI server,488,ActiveX|ADO
1590,SAP BI 4.2 Sp5,173,SAP BusinessObjects BI server,174,SAP ERP
1593,SAP HANA ON SUSEOracle 11g on Linux,175,SAP HANA DB,435,Linux|SUSE Linux Enterprise Server
1596,NetWeaver,279,SAP NetWeaver App Server,431,Linux|openSUSE
1605,SCSS,361,Sass,102,Microsoft Endpoint Configuration Manager (SCCM)
1606,Scalla,362,Scala,664,Forte
1609,Microsoft SPS 2010,603,SharePoint|*,577,MVS|*
1613,SQL Server SP2013 Database Server,603,SharePoint|*,581,MS SQL Server|*
1615,Siebel IP 2015,182,Siebel,583,C++|*
1616,Siebel 7.8.2.16,182,Siebel,43,DB2
1617,Siebel CRM,182,Siebel,583,C++|*
1619,Techsmith Corporation - SnagIt 8,184,SnagIt,183,SNA Manager
1620,Solid development server,185,solidDB,600,Oracle WebLogic Server|*
1622,Sixty-Five Software - SpaceMonger 1.4,187,SpaceMonger,296,Intel Xeon Processor
1623,SQLPlus,478,Oracle Database|SQL*Plus,572,Structured Query Language (SQL)
1625,SQLIO 1.0,189,SQLIO,178,SAP SQL Anywhere
1630,SunOne,281,Oracle iPlanet Web Server,448,Unix|BSD|SunOS
1637,SAP - Sybase Central 4.3,479,Sybase SQL Server|Sybase Central,190,Sybase SQL Server
1639,Sysncsort,191,Syncsort,178,SAP SQL Anywhere
1640,syncsort,191,Syncsort,98,Memcached
1641,Sysinternals LLC - AccessEnum 1 1,194,Sysinternal Tools|AccessEnum,124,Nexus Repository OSS
1642,Sysinternals LLC - ClockRes 2,195,Sysinternal Tools|ClockRes,374,Xbase++
1643,Sysinternals LLC - Coreinfo 3.21,196,Sysinternal Tools|Coreinfo,670,EAServer
1644,Sysinternals LLC - DiskExt 1.1,197,Sysinternal Tools|DiskExt,374,Xbase++
1645,Sysinternals LLC - DiskMon 2.01,198,Sysinternal Tools|DiskMon,670,EAServer
1647,Sysinternals LLC - Junction 1.6,200,Sysinternal Tools|Junction,374,Xbase++
1648,Sysinternals LLC - LDMDump 1.02,201,Sysinternal Tools|LDMDump,178,SAP SQL Anywhere
1649,Sysinternals LLC - LoadOrder 1,202,Sysinternal Tools|LoadOrder,374,Xbase++
1650,Sysinternals LLC - PipeList 1.01,203,Sysinternal Tools|PipeList,670,EAServer
1651,Sysinternals LLC - Process Explorer 16.5,204,Sysinternal Tools|Process Explorer,464,Microsoft Exchange Server|Veeam Explorer
1652,Sysinternals LLC - PsKill 1.15,205,Sysinternal Tools|PsKill,151,PeopleSoft
1653,Sysinternals LLC - PsPasswd 1.23,206,Sysinternal Tools|PsPasswd,231,VMware vCenter
1654,Sysinternals LLC - SDelete 1.61,207,Sysinternal Tools|SDelete,670,EAServer
1655,Sysinternals LLC - ShareEnum 1.6,208,Sysinternal Tools|ShareEnum,603,SharePoint|*
1656,Sysinternals LLC - Sync 2.2,209,Sysinternal Tools|Sync,374,Xbase++
1657,Sysinternals LLC - Sysinternals TCPView 3.5,210,Sysinternal Tools|TCPView,365,TCL
1658,Sysinternals LLC - VMMap 3.11,211,Sysinternal Tools|VMMap,176,SAP MaxDB
1659,Sysinternals LLC - Whois 1.11,212,Sysinternal Tools|Whois,178,SAP SQL Anywhere
1664,TERADATA QUERY SCHEDULER SERVER VERSION 15,216,Teradata QS Server,215,Teradata
1667,BusinessWorks,217,TIBCO Business Works (BW),111,Microsoft Visual Studio
1668,Tibco-IM,481,TIBCO Business Works (BW)|Integration Manager,219,TIBCO Rendezvous
1669,Tibco Integration Manager,481,TIBCO Business Works (BW)|Integration Manager,219,TIBCO Rendezvous
1674,TSQL,366,Transact-SQL,621,ArangoDB
1675,Trasact SQL,366,Transact-SQL,352,PL/SQL
1746,Solaris 11.2 SPARC,448,Unix|BSD|SunOS,375,Apache Lucene
1747,Solaris UNIX,448,Unix|BSD|SunOS,578,Unix|*
1748,Unix Servers (Solaris,448,Unix|BSD|SunOS,578,Unix|*
1749,Oracle Solaris 11.3 SPARC,448,Unix|BSD|SunOS,375,Apache Lucene
1753,Solaris 5.10 (Generic_150400-61),448,Unix|BSD|SunOS,521,Electronic Data Interchange (EDI)
1754,Solaris 5.10 (Generic_150400-62),448,Unix|BSD|SunOS,521,Electronic Data Interchange (EDI)
1756,Solaris 5.10 (Generic_150400-55),448,Unix|BSD|SunOS,521,Electronic Data Interchange (EDI)
1760,Oracle Solaris,448,Unix|BSD|SunOS,134,Oracle Database
1762,Solaris 1 (SPARC),448,Unix|BSD|SunOS,375,Apache Lucene
1765,SunSolaris 10.0,448,Unix|BSD|SunOS,430,Linux|Junos OS
1771,Oracle Solaris 10,448,Unix|BSD|SunOS,134,Oracle Database
1800,VIO 2.2.0.10,227,Virtual I/O Server,159,Primavera P6
1801,VIOS,227,Virtual I/O Server,443,OS/2
1802,visibroker,228,Visibroker,420,Cisco IOS
1803,VB6,370,Visual Basic,368,VB.NET
1804,VB 6.0,370,Visual Basic,368,VB.NET
1805,visualbasic,370,Visual Basic,306,C++|Visual C++
1808,Visual Basic 6.0,370,Visual Basic,368,VB.NET
1811,VBA,371,Visual Basic for Applications (VBA),370,Visual Basic
1812,Access VB,371,Visual Basic for Applications (VBA),99,Microsoft Access
1813,vfoxpro,372,Visual FoxPro,117,Mozilla Firefox
1827,VMware Appliance,569,VMware Server,559,Virtual Appliance
1828,VSX,229,VMware Solution Exchange Marketplace (VSX),111,Microsoft Visual Studio
1830,VMware - VMware Tools 10.2,230,VMware Tools,569,VMware Server
1832,VXML,373,VoiceXML,316,eXtensible HyperText Markup Language (XHTML)
1833,Web Focus,232,WebFOCUS,321,FOCUS
1834,FOCEXEC,232,WebFOCUS,495,Oracle WebCenter Content Server|Idoc Script
1836,WLI 8,233,WebLogic Integration,442,OpenVMS
1842,IBM WEBSPHERE APPLICATION SERVER VERSION 6.1.0,284,Websphere Application Server (WAS),285,WebSphere Liberty
1848,"IBM WebSphere Application Server Network Deployment, 8.0.0.5",284,Websphere Application Server (WAS),285,WebSphere Liberty
1850,IBM WebSphere Application Server Network Deployment 7,284,Websphere Application Server (WAS),285,WebSphere Liberty
1858,IBM WebSphere 8.5,284,Websphere Application Server (WAS),285,WebSphere Liberty
1861,IBM - WebSphere Application Server - Base 8.5,284,Websphere Application Server (WAS),285,WebSphere Liberty
1865,Websphere AS (JVM),284,Websphere Application Server (WAS),285,WebSphere Liberty
1872,IBM WebSphere,284,Websphere Application Server (WAS),285,WebSphere Liberty
1875,IBM WebSphere Application Server 8.5,284,Websphere Application Server (WAS),285,WebSphere Liberty
1877,IBM WebSphere Application,284,Websphere Application Server (WAS),285,WebSphere Liberty
1878,WAS 6.x,284,Websphere Application Server (WAS),521,Electronic Data Interchange (EDI)
1880,IBM OpenStack Liberty,285,WebSphere Liberty,431,Linux|openSUSE
1882,Open Liberty,285,WebSphere Liberty,397,Java|Servlet
1883,IBM Open Liberty,285,WebSphere Liberty,62,IBM BigFix Platform
1887,WAS Liberty,285,WebSphere Liberty,397,Java|Servlet
1889,OpenStack Liberty,285,WebSphere Liberty,431,Linux|openSUSE
1891,WMB 6.1,235,WebSphere Message Broker,486,.NET Framework|Windows Workflow Foundation (WF)
1892,WebSphere Message Broker v6.0,235,WebSphere Message Broker,285,WebSphere Liberty
1899,WebSphere Portal Extend Limited Use 6.1,286,WebSphere Portal Server,285,WebSphere Liberty
1901,Windchill 11.1,237,Windchill,17,Bluebeam|Bluebeam Q
1908,Window,580,Windows|*,637,Microsoft Azure
1914,Windows Terminal Server,239,Windows Terminal Server (WTS),452,Windows|Windows Server
1915,Windows 7 Standard,451,Windows|Windows Desktop,580,Windows|*
1916,WINDOWS 10 SERVER STANDARD EDITION X64,451,Windows|Windows Desktop,452,Windows|Windows Server
1917,Microsoft Windows 7 (64-bit),451,Windows|Windows Desktop,580,Windows|*
1918,Microsoft Windows XP Professional (32-bit),451,Windows|Windows Desktop,580,Windows|*
1919,Windows 7 Professional x64,451,Windows|Windows Desktop,580,Windows|*
1920,Microsoft Microsoft Windows Entreprise,451,Windows|Windows Desktop,580,Windows|*
1921,Microsoft Windows 2000,451,Windows|Windows Desktop,580,Windows|*
1922,Microsoft Windows 10,451,Windows|Windows Desktop,580,Windows|*
1923,MS Microsoft Windows 7,451,Windows|Windows Desktop,580,Windows|*
1924,Microsoft Windows 7 Professional,451,Windows|Windows Desktop,580,Windows|*
1925,Microsoft Microsoft Windows 7 Enterprise,451,Windows|Windows Desktop,580,Windows|*
1926,Microsoft Windows 10 Enterprise,451,Windows|Windows Desktop,580,Windows|*
1927,Win Desktop,451,Windows|Windows Desktop,560,Webtop
1928,Windows 10 Pro,451,Windows|Windows Desktop,580,Windows|*
1929,Windows 10,451,Windows|Windows Desktop,580,Windows|*
1930,Windows 7 Ultimate,451,Windows|Windows Desktop,580,Windows|*
1931,Microsoft Windows 8 (64-bit),451,Windows|Windows Desktop,580,Windows|*
1932,Microsoft Windows XP,451,Windows|Windows Desktop,580,Windows|*
1933,Windows 10 Enterprise,451,Windows|Windows Desktop,580,Windows|*
1934,Windows XP,451,Windows|Windows Desktop,580,Windows|*
1935,Windows 10 Professional,451,Windows|Windows Desktop,580,Windows|*
1936,Windows 7,451,Windows|Windows Desktop,580,Windows|*
1937,Microsoft Windows 10 (64-bit),451,Windows|Windows Desktop,580,Windows|*
1938,Win 7,451,Windows|Windows Desktop,333,Java|Java Enterprise Edition (Java EE)
1939,windowsxp,451,Windows|Windows Desktop,580,Windows|*
1940,Microsoft Windows Unknown,451,Windows|Windows Desktop,580,Windows|*
1941,Windows 7 Enterprise,451,Windows|Windows Desktop,580,Windows|*
1942,Windows XP Professional,451,Windows|Windows Desktop,580,Windows|*
1943,Windows 7 Professional,451,Windows|Windows Desktop,580,Windows|*
1944,Window XP,451,Windows|Windows Desktop,580,Windows|*
1945,Microsoft Windows 7 Enterprise,451,Windows|Windows Desktop,580,Windows|*
1946,Microsoft Windows 7 - SOE,451,Windows|Windows Desktop,580,Windows|*
1947,Windows 7 Enterprise Edition,451,Windows|Windows Desktop,452,Windows|Windows Server
1948,Windows 8,451,Windows|Windows Desktop,580,Windows|*
1949,Microsoft Windows 7,451,Windows|Windows Desktop,580,Windows|*
1950,Microsoft Windows 7 (32-bit),451,Windows|Windows Desktop,580,Windows|*
1951,Windows Embedded Standard 7,451,Windows|Windows Desktop,580,Windows|*
1952,Win10,451,Windows|Windows Desktop,333,Java|Java Enterprise Edition (Java EE)
1953,Windows 2003,451,Windows|Windows Desktop,580,Windows|*
1955,Windows 2003 Standard,452,Windows|Windows Server,580,Windows|*
1956,Windows 2008 Enterprise R2 x64,452,Windows|Windows Server,580,Windows|*
1960,WINDOWS 2008R2,452,Windows|Windows Server,580,Windows|*
1961,Microsoft Windows Server 2008 Standard Editio,452,Windows|Windows Server,121,MS SQL Server Compact
1962,MICROSOFT WINDOWS NT 2003,452,Windows|Windows Server,580,Windows|*
1967,Microsoft Microsoft Windows Server 2016 Datacenter,452,Windows|Windows Server,276,Oracle WebCenter Content Server
1979,Windows 2008 Enterprise 32-bit,452,Windows|Windows Server,580,Windows|*
1982,Windows 2003 R2,452,Windows|Windows Server,580,Windows|*
1983,Windows 2008 R2 Enterprise 64 Bit,452,Windows|Windows Server,580,Windows|*
1988,Windows 2008 R2,452,Windows|Windows Server,580,Windows|*
1989,Windows 2012 Standard,452,Windows|Windows Server,580,Windows|*
1992,Windows 2008 R2 Standard 6.1.7601 Service Pack 1,452,Windows|Windows Server,580,Windows|*
1994,Windows 2008 Standard x64,452,Windows|Windows Server,580,Windows|*
1998,Windows 2012 R2 Standard 64-Bit,452,Windows|Windows Server,580,Windows|*
2007,w2k12,452,Windows|Windows Server,582,C#|*
2008,WINDOWS 2013,452,Windows|Windows Server,580,Windows|*
2009,WINDOWS 2016 SE 64 BIT,452,Windows|Windows Server,580,Windows|*
2011,Microsoft - Windows 2012,452,Windows|Windows Server,580,Windows|*
2019,MICROSOFT WINDOWS 2008 TPM,452,Windows|Windows Server,580,Windows|*
2021,MICROSOFT WINDOWS STD 2008,452,Windows|Windows Server,580,Windows|*
2025,Windows 2008 R2 Standard 64 Bit,452,Windows|Windows Server,580,Windows|*
2028,MICROSOFT WINDOWS STD 2008 TPM,452,Windows|Windows Server,580,Windows|*
2030,Windows 2012 64 Bit,452,Windows|Windows Server,580,Windows|*
2031,MICROSOFT WINDOWS NT 2003 ENT,452,Windows|Windows Server,580,Windows|*
2034,MICROSOFT WINDOWS 2012,452,Windows|Windows Server,580,Windows|*
2036,Windows 2003 Standard5.2.3790,452,Windows|Windows Server,580,Windows|*
2040,Windows 2012 R,452,Windows|Windows Server,580,Windows|*
2044,Windows 2008 Enterprise 32 Bit,452,Windows|Windows Server,580,Windows|*
2045,MICROSOFT WINDOWS 2008 ENT,452,Windows|Windows Server,580,Windows|*
2047,Windows 2012 R2 Standard 6.3.9600,452,Windows|Windows Server,580,Windows|*
2053,Windows 2016 Datacenter,452,Windows|Windows Server,276,Oracle WebCenter Content Server
2055,Microsoft Windows Server 2016 Datacenter,452,Windows|Windows Server,276,Oracle WebCenter Content Server
2061,Windows 2016 Datacenter10.0.14393,452,Windows|Windows Server,637,Microsoft Azure
2065,windows6.3.9600,452,Windows|Windows Server,580,Windows|*
2066,Windows 2012 R2 Standard 64 Bit,452,Windows|Windows Server,580,Windows|*
2069,Windows 2008 Enterprise,452,Windows|Windows Server,580,Windows|*
2080,Windows 2008 Standard without Hyper-V6.0.6003,452,Windows|Windows Server,580,Windows|*
2084,Windows 2012 R2 Datacenter,452,Windows|Windows Server,110,Microsoft System Center Endpoint Protection
2089,Windows 2008 Standard 64-bit,452,Windows|Windows Server,580,Windows|*
2096,Windows 2000,452,Windows|Windows Server,580,Windows|*
2097,W2K8R2 Standard 64 BIT,452,Windows|Windows Server,303,C
2099,Windows 2008 Standard6.0.6003,452,Windows|Windows Server,580,Windows|*
2100,Windows2008 R2 Enterprise 64bit,452,Windows|Windows Server,580,Windows|*
2105,Win2008R2,452,Windows|Windows Server,355,R
2107,Windows 2008 Standard 64 Bit,452,Windows|Windows Server,580,Windows|*
2109,Windows Server 2003 Appliance,452,Windows|Windows Server,559,Virtual Appliance
2111,Windows 2008 ENT R2 (64 bits),452,Windows|Windows Server,355,R
2114,WIN2008R2 6.1.7601,452,Windows|Windows Server,355,R
2116,microsoft windows std 2012 tpm,452,Windows|Windows Server,580,Windows|*
2118,microsoft windows 2008,452,Windows|Windows Server,580,Windows|*
2120,Windows 2008 Standard 32 Bit,452,Windows|Windows Server,580,Windows|*
2121,Microsoft Windows 2008 R2 Standard,452,Windows|Windows Server,580,Windows|*
2126,Window2008 R2,452,Windows|Windows Server,355,R
2130,Windows 2008 Standard,452,Windows|Windows Server,580,Windows|*
2134,WS03,452,Windows|Windows Server,239,Windows Terminal Server (WTS)
2136,Windows 2008 Enterprise x64,452,Windows|Windows Server,580,Windows|*
2141,Windows 2008 R2 Enterprise,452,Windows|Windows Server,580,Windows|*
2142,Windows Server 2003 Std 32-bit,452,Windows|Windows Server,580,Windows|*
2143,Windows 2008 R2 Standard 64bit,452,Windows|Windows Server,580,Windows|*
2146,Microsoft Windows 2003 R2 Standard,452,Windows|Windows Server,580,Windows|*
2148,MICROSOFT WINDOWS NT 2003 TPM,452,Windows|Windows Server,580,Windows|*
2149,Win Server 2008,452,Windows|Windows Server,569,VMware Server
2150,Windows 2003 R2 Standard 64 Bit,452,Windows|Windows Server,580,Windows|*
2152,WIN2014,452,Windows|Windows Server,333,Java|Java Enterprise Edition (Java EE)
2156,Win 2012 R2,452,Windows|Windows Server,355,R
2160,Win Server,452,Windows|Windows Server,12,Apache Subversion
2161,Windows 2008 Standard R2 x64,452,Windows|Windows Server,580,Windows|*
2163,Windows server 2008 Dual processor Intel Xeon x5660 @2.80 GHz 6196 MB memory installed,452,Windows|Windows Server,296,Intel Xeon Processor
2164,Windows2012,452,Windows|Windows Server,580,Windows|*
2165,Windows 2008 R2 Standard6.1.7601,452,Windows|Windows Server,580,Windows|*
2166,Windows 2016,452,Windows|Windows Server,580,Windows|*
2167,Windows 2008 R2 Standard,452,Windows|Windows Server,580,Windows|*
2179,Windows Server 2003 Std 64-bit,452,Windows|Windows Server,580,Windows|*
2180,Windows 2012 R2,452,Windows|Windows Server,580,Windows|*
2181,Wintel,452,Windows|Windows Server,461,IBM Tivoli Storage Manager|TSM Client
2191,Windows 2003 Enterprise5.2.3790,452,Windows|Windows Server,580,Windows|*
2192,WINDOWS 2012,452,Windows|Windows Server,580,Windows|*
2193,Windows 2008 R2 OS,452,Windows|Windows Server,580,Windows|*
2196,Windows 2003 Standard R2,452,Windows|Windows Server,580,Windows|*
2197,Windows 2008 R2 Enterprise6.1.7601,452,Windows|Windows Server,580,Windows|*
2198,Windows 2003 Standard 32 Bit,452,Windows|Windows Server,580,Windows|*
2199,WINDOWS SERVER 2003 APPLIANCE 5.2,452,Windows|Windows Server,559,Virtual Appliance
2201,WS08R2,452,Windows|Windows Server,355,R
2204,Windows 2008 Enterprise 64 Bit,452,Windows|Windows Server,580,Windows|*
2213,w2k8r2sp1,452,Windows|Windows Server,355,R
2217,Win 2003,452,Windows|Windows Server,333,Java|Java Enterprise Edition (Java EE)
2222,Windows 2012 R2 Standard,452,Windows|Windows Server,580,Windows|*
2226,Windows 2008 R2 Standard 64-bit,452,Windows|Windows Server,580,Windows|*
2228,Windows 2003 Enterprise 32-bit,452,Windows|Windows Server,580,Windows|*
2230,Windows 2012 Storage R2,452,Windows|Windows Server,580,Windows|*
2231,Windows server 2008 Dual processor Intel Xeon x5660 @2.80 GHz 4096 MB memory installed,452,Windows|Windows Server,296,Intel Xeon Processor
2235,MICROSOFT WINDOWS NT 2003 ENT TPM,452,Windows|Windows Server,239,Windows Terminal Server (WTS)
2237,Windows 2016 Standard10.0.14393,452,Windows|Windows Server,580,Windows|*
2240,MICROSOFT WINDOWS 2003,452,Windows|Windows Server,580,Windows|*
2242,Windows 2012 Standard R2,452,Windows|Windows Server,580,Windows|*
2246,Win Server 2008 R2,452,Windows|Windows Server,355,R
2248,MICROSOFT WINDOWS STD 2012 TPM,452,Windows|Windows Server,580,Windows|*
2249,Windows 2003 Enterprise 32 Bit,452,Windows|Windows Server,580,Windows|*
2250,Windows 2008 Enterprise R2,452,Windows|Windows Server,580,Windows|*
2251,Windows 2008,452,Windows|Windows Server,580,Windows|*
2252,Microsoft Microsoft Windows 2008 R2,452,Windows|Windows Server,580,Windows|*
2257,Win Server 2012,452,Windows|Windows Server,569,VMware Server
2258,Windows 2016 Standard,452,Windows|Windows Server,580,Windows|*
2264,Windows 2008 Enterprise 64-bit,452,Windows|Windows Server,580,Windows|*
2267,Windows 2003 Standard 5.2.3790 Service Pack 2,452,Windows|Windows Server,580,Windows|*
2268,Windows 2012 Standard6.2.9200,452,Windows|Windows Server,580,Windows|*
2269,MICROSOFT WINDOWS 2016 TPM,452,Windows|Windows Server,580,Windows|*
2272,Windows 2003 Enterprise,452,Windows|Windows Server,580,Windows|*
2275,Windows 2008 R2 Enterprise 64-bit,452,Windows|Windows Server,580,Windows|*
2277,Windows 2012 R2 Standard6.3.9600,452,Windows|Windows Server,580,Windows|*
2286,Windows 2008 Standard R2,452,Windows|Windows Server,580,Windows|*
2287,MicrosoftWindows Server 2008 R2 (64-bit),452,Windows|Windows Server,443,OS/2
2288,windows6.3,452,Windows|Windows Server,580,Windows|*
2290,Windows 2016 64 Bit,452,Windows|Windows Server,580,Windows|*
2296,Windows 2008 Enterprise6.0.6003,452,Windows|Windows Server,580,Windows|*
2301,Win 2012,452,Windows|Windows Server,333,Java|Java Enterprise Edition (Java EE)
2302,Win2012,452,Windows|Windows Server,333,Java|Java Enterprise Edition (Java EE)
2303,Win2012R2,452,Windows|Windows Server,355,R
2305,win2008,452,Windows|Windows Server,333,Java|Java Enterprise Edition (Java EE)
2306,Windows 2003 Standard x64,452,Windows|Windows Server,580,Windows|*
2315,WINDOWS 2016 STANDARD EDITION,452,Windows|Windows Server,580,Windows|*
2325,WinSCP.net - WinSCP 5.11,243,WinSCP,178,SAP SQL Anywhere
2332,Zerto Vritual Appliance,249,Zerto Virtual Replication,559,Virtual Appliance
2333,Oracle RTD,289,Oracle Real-Time Decisions (RTD),134,Oracle Database
2338,OMNIbus,251,Tivoli Netcool/OMNIbus,582,C#|*
2347,ALM,511,Application Lifecycle Management (ALM),421,DART
2349,BMS,513,Batch Management Software (BMS),442,OpenVMS
2354,COM,516,Compopent Object Model (COM),661,COM+
2357,CORBA Interface Definition Language,518,CORBA Interface Definition Language (CORBA IDL),517,Common Object Request Broker Architecture (CORBA)
2359,Data Control Language,519,Data Control Language (DCL),329,IBM i Control Language (CL)
2361,Database,520,Database (DB),43,DB2
2362,DB,520,Database (DB),43,DB2
2365,Electronic Data Interchange,521,Electronic Data Interchange (EDI),104,Microsoft Exchange Server
2369,JDOM,523,Java-based Document Object Model for XML (JDOM),84,IMS DB
2381,Simple Object Access Protocol,531,Simple Object Access Protocol (SOAP),547,Internet Message Access Protocol (IMAP)
2383,SQL,572,Structured Query Language (SQL),581,MS SQL Server|*
2386,DPE,538,Device Provisioning Engines (DPE),661,COM+
2388,ESB,540,Enterprise Service Bus(ESB),370,Visual Basic
2395,MES,553,Manufacturing Execution System (MES),623,Amazon S3
2401,Z/Virtual System Environment,591,z/VSE,441,MVS|z/OS
2403,DOS/VSE,591,z/VSE,597,DOS/360
2404,Microsoft Disk Operating System,593,MS-DOS,443,OS/2
2407,VME/B,595,VME,368,VB.NET
2408,Virtual Machine Environment,595,VME,111,Microsoft Visual Studio
2409,VME 2900,595,VME,107,Microsoft Internet Explorer
2410,OpenVME,595,VME,442,OpenVMS
2411,Disk Operating System/360,597,DOS/360,443,OS/2
2413,Transaction Processing Facility,598,z/TPF,572,Structured Query Language (SQL)
2419,NPL,653,Natural Programming Language,342,Niakwa Programming Language (NPL)
2426,IDMS/DB Data Manipulation Language,668,IDMS DML,312,Data Language Interface (DL/I)
2433,Basic Mapping Supprt,689,BMS Map,21,Business Intelligence and Reporting Tools (BIRT)
2434,DB/400,690,DB400,43,DB2
2435,IBM ISAM,693,ISAM,73,IBM Operational Decision Manager (ODM)
1 mention entity_id entity_name class_prediction predicted_name
2 0 DOT NET 497 .NET Framework 579 Unix|BSD|*
3 2 Dot net - FW 4 497 .NET Framework 368 VB.NET
4 3 .Net 4.7.1 Enterprise Lib 497 .NET Framework 368 VB.NET
5 11 .NET 497 .NET Framework 579 Unix|BSD|*
6 13 .Net 4.5.2 Enterprise Lib 497 .NET Framework 368 VB.NET
7 40 APACHE LOG4NET 483 .NET Framework|log4net 394 Java|Log4j
8 41 LOG4NET 483 .NET Framework|log4net 394 Java|Log4j
9 42 Magik 484 .NET Framework|Magick.NET 533 YAML
10 43 WCF 485 .NET Framework|Windows Communication Foundation (WCF) 486 .NET Framework|Windows Workflow Foundation (WF)
11 45 WWF 486 .NET Framework|Windows Workflow Foundation (WF) 443 OS/2
12 47 Ejes 1 (E)JES 101 Microsoft Dynamics AX
13 48 (UNIRITA) A-AUTO 7.2.2 2 A-Auto Job Scheduling Software 299 AutoIt
14 50 Active Directoy 498 Active Directory (AD) 40 Connect Direct
15 54 APSX 592 Active Server Pages (ASP)|* 609 IIS|*
16 69 Andriod 418 Android 586 PHP|*
17 71 Apache Active Queue 6 Apache ActiveMQ 259 Apache HTTP Server
18 72 MQ Apache Active Queue 6 Apache ActiveMQ 81 IBM Websphere MQ
19 75 cordova-android 501 Apache Cordova 418 Android
20 77 Hive 8 Apache Hive 177 SAP NetWeaver Business Warehouse
21 99 solr 11 Apache Solr 375 Apache Lucene
22 135 ADF 13 Application Development Facility (ADF) 130 Oracle ADF
23 144 WLS 10.2 600 Oracle WebLogic Server|* 442 OpenVMS
24 149 BEA WLS 600 Oracle WebLogic Server|* 442 OpenVMS
25 152 Weblogic 12c 600 Oracle WebLogic Server|* 582 C#|*
26 160 WLE 600 Oracle WebLogic Server|* 443 OS/2
27 168 Web Logic 600 Oracle WebLogic Server|* 97 MarkLogic DB
28 174 BEA WLE 600 Oracle WebLogic Server|* 443 OS/2
29 175 WLS 10 600 Oracle WebLogic Server|* 442 OpenVMS
30 176 WLS 600 Oracle WebLogic Server|* 442 OpenVMS
31 189 brain script 302 Brainscript 369 VBScript
32 190 BRAINScript 302 Brainscript 367 TypeScript
33 191 Business Intelligence and Reporting Tools 21 Business Intelligence and Reporting Tools (BIRT) 133 Oracle Business Intelligence
34 192 Actuate Report Server 21 Business Intelligence and Reporting Tools (BIRT) 42 Crystal Reports
35 194 CSHARP 582 C#|* 87 Informatica PowerCenter
36 218 WinFrame 30 Citrix Virtual Apps and Desktops 443 OS/2
37 221 METAFRAME 30 Citrix Virtual Apps and Desktops 406 JavaScript|AngularJS
38 225 Presentation Server 30 Citrix Virtual Apps and Desktops 541 File Server
39 226 NETSCALER-1.5 563 Citrix ADC 273 Netscape Enterprise Server (NES)
40 227 NETSCALER-11. 563 Citrix ADC 273 Netscape Enterprise Server (NES)
41 228 Citrix SD-WAN 563 Citrix ADC 30 Citrix Virtual Apps and Desktops
42 229 NetScaler SD-WAN 563 Citrix ADC 273 Netscape Enterprise Server (NES)
43 231 NetScaler ADC 563 Citrix ADC 272 Netscape Application Server (NAS)
44 236 NetScaler SDX 291 Citrix ADC SDX 273 Netscape Enterprise Server (NES)
45 240 Provisioning Services 7.15.8 32 Citrix Provisioning 538 Device Provisioning Engines (DPE)
46 241 Citrix PVS 32 Citrix Provisioning 30 Citrix Virtual Apps and Desktops
47 243 CLISTS 309 CLIST 329 IBM i Control Language (CL)
48 253 CFML 311 ColdFusion Markup Language (CFML) 316 eXtensible HyperText Markup Language (XHTML)
49 254 ColdFusion Markup Language 311 ColdFusion Markup Language (CFML) 37 Coldfusion
50 255 Sterling Connect 40 Connect Direct 542 General Ledger
51 264 Cormerstone 41 Cornerstone software 516 Compopent Object Model (COM)
52 265 Cornerstone 41 Cornerstone software 370 Visual Basic
53 279 DB2 UDB 43 DB2 517 Common Object Request Broker Architecture (CORBA)
54 282 DB2-UDB 43 DB2 365 TCL
55 291 DB2/UDB 43 DB2 365 TCL
56 292 IBM DB2 ENTERPRISE SERVER EDITION PVU OPTION 10.5 43 DB2 163 PVCS Version Manager
57 300 IBM - IBM DB2 Advanced Enterprise Server Edition PVU Option 10.5 43 DB2 72 IBM Mobile Foundation
58 301 UDB 43 DB2 517 Common Object Request Broker Architecture (CORBA)
59 302 IBM - IBM DB2 Enterprise Server Edition Product Trial 9.7 43 DB2 610 Oracle Application Server|*
60 306 IBM - IBM DB2 Workgroup Server Edition Product Trial 9.7 43 DB2 610 Oracle Application Server|*
61 313 EZTriev 314 Easytrieve 296 Intel Xeon Processor
62 314 Eztrieve 314 Easytrieve 296 Intel Xeon Processor
63 321 PrestoSoft - ExamDiff Application 1.6 49 ExamDiff 346 Pascal|Object Pascal
64 322 PrestoSoft - ExamDiff Application 49 ExamDiff 346 Pascal|Object Pascal
65 323 ExamDiff Application 49 ExamDiff 467 MS SQL Server|Log Reader Agent
66 324 Expect Scripts 315 Expect 109 Microsoft MQ
67 329 Microsoft - MSXML 4.0 SP2 4.2 318 Extensible Markup Language (XML)|MSXML 316 eXtensible HyperText Markup Language (XHTML)
68 331 XSL 319 Extensible Stylesheet Language (XSL) 320 Extensible Stylesheet Language Transformations (XLST)
69 332 JAVA-XSL 319 Extensible Stylesheet Language (XSL) 320 Extensible Stylesheet Language Transformations (XLST)
70 335 ServerCA Access GatewayF5 50 F5 Secure Web Gateway Services 290 CA API Gateway
71 347 HP C++ 58 HP aC++ compiler 59 HP C/ANSI C compiler
72 350 HP C++ 10.20 58 HP aC++ compiler 59 HP C/ANSI C compiler
73 351 HPC 11.11 59 HP C/ANSI C compiler 58 HP aC++ compiler
74 358 HFS 505 HTTP File Server 486 .NET Framework|Windows Workflow Foundation (WF)
75 359 www.rejetto.com - HttpFileServer 2.3 505 HTTP File Server 55 Google Chrome
76 360 HttpFileServer 505 HTTP File Server 522 Application Web Server
77 367 IBM - IBM BigFix Platform Client Deploy Tool 9.5 457 IBM BigFix Platform|Client Deploy Tool 62 IBM BigFix Platform
78 369 IBM BPM 64 IBM Business Process Manager 328 IBM High Level Assembler (HLASM)
79 375 Data Power 294 IBM DataPower Gateway 295 IBM Power Systems
80 376 IDG.7.5.2.19hp 294 IBM DataPower Gateway 449 Unix|HP-UX
81 380 hlasm 328 IBM High Level Assembler (HLASM) 438 macOS
82 383 IHS 265 IBM HTTP Server 424 IBM i
83 386 WebSphere and IHS 265 IBM HTTP Server 67 IBM InfoSphere DataStage
84 387 WebSphere http 265 IBM HTTP Server 284 Websphere Application Server (WAS)
85 391 IBM Websphere HTTP Server 265 IBM HTTP Server 285 WebSphere Liberty
86 393 WebSphere IHS 265 IBM HTTP Server 601 Websphere ILOG JRules BRMS
87 394 WebSphere -IHS 265 IBM HTTP Server 601 Websphere ILOG JRules BRMS
88 397 OS400 V7R1 424 IBM i 443 OS/2
89 398 OS400 424 IBM i 443 OS/2
90 399 OS/400 424 IBM i 443 OS/2
91 408 IIB 68 IBM Integration Bus 370 Visual Basic
92 411 Extended Structured Query Language 458 IBM Integration Bus|Extended Structured Query Language (ESQL) 572 Structured Query Language (SQL)
93 415 IBM WorkLight 72 IBM Mobile Foundation 649 IBM Cloud
94 417 ILOG JRules 73 IBM Operational Decision Manager (ODM) 601 Websphere ILOG JRules BRMS
95 420 Decision Center 8.0.1.0 73 IBM Operational Decision Manager (ODM) 252 IBM ILOG Views
96 423 AS400 295 IBM Power Systems 443 OS/2
97 424 AS/400 295 IBM Power Systems 443 OS/2
98 426 System i 295 IBM Power Systems 424 IBM i
99 427 P-series 295 IBM Power Systems 81 IBM Websphere MQ
100 428 IBM iSeries/AS400 system Model 520 295 IBM Power Systems 443 OS/2
101 439 Tivoli Asset Discovery for Distributed 459 IBM Tivoli Asset Management|Asset Discovery for Distributed 606 IBM Tivoli Asset Management|*
102 447 Database MS SQL Agent 77 IBM Tivoli Monitoring 469 MS SQL Server|SQL Server Database Engine
103 448 Linux OS Agent 77 IBM Tivoli Monitoring 576 Linux|*
104 449 Database DB2 Agent 77 IBM Tivoli Monitoring 520 Database (DB)
105 452 Windows OS Agent 77 IBM Tivoli Monitoring 580 Windows|*
106 454 IBM - IBM TSM FCM 604 IBM Tivoli Storage Manager|* 460 IBM Tivoli Storage Manager|TSM API
107 459 Databases Data Protection for Microsoft SQL 604 IBM Tivoli Storage Manager|* 572 Structured Query Language (SQL)
108 461 IBM - IBM Spectrum Protect Data Protection for Microsoft SQL Server 8.1 604 IBM Tivoli Storage Manager|* 469 MS SQL Server|SQL Server Database Engine
109 462 IBM Spectrum Protect Data Protection 604 IBM Tivoli Storage Manager|* 312 Data Language Interface (DL/I)
110 463 IBM - IBM Spectrum Protect API 7.1 460 IBM Tivoli Storage Manager|TSM API 294 IBM DataPower Gateway
111 464 IBM - IBM Spectrum Protect Client 461 IBM Tivoli Storage Manager|TSM Client 294 IBM DataPower Gateway
112 465 IBM - IBM Tivoli Storage Manager Client 461 IBM Tivoli Storage Manager|TSM Client 604 IBM Tivoli Storage Manager|*
113 467 VSS Requestor configured 8.1 463 IBM Tivoli Storage Manager|VSS Requestor 577 MVS|*
114 468 VSS Requestor 7.1 463 IBM Tivoli Storage Manager|VSS Requestor 577 MVS|*
115 469 TWS-WS 79 IBM Tivoli Workload Scheduler (TWS) 239 Windows Terminal Server (WTS)
116 472 wbia 2.6 80 IBM WebSphere Business Integration Adaptor 627 XtraDB
117 473 IBM WBIA 2.6.0.12 80 IBM WebSphere Business Integration Adaptor 424 IBM i
118 475 MQ 81 IBM Websphere MQ 248 ZeroMQ
119 476 MQ 9.1 81 IBM Websphere MQ 248 ZeroMQ
120 479 MQ 7 81 IBM Websphere MQ 248 ZeroMQ
121 480 MQ 6 81 IBM Websphere MQ 248 ZeroMQ
122 481 MQ 9.0 81 IBM Websphere MQ 248 ZeroMQ
123 482 MQ 5.3 81 IBM Websphere MQ 248 ZeroMQ
124 483 MQ 7.01 81 IBM Websphere MQ 248 ZeroMQ
125 484 MQ 7.5 81 IBM Websphere MQ 248 ZeroMQ
126 485 MQSeries 8.0 81 IBM Websphere MQ 248 ZeroMQ
127 488 WSMQ 8.0 81 IBM Websphere MQ 248 ZeroMQ
128 489 MQ 9.0.5 81 IBM Websphere MQ 248 ZeroMQ
129 491 WTX 83 IBM WebSphere Transformation Extender (WTX) 274 Nginx
130 505 Microsoft Internet Inf 609 IIS|* 130 Oracle ADF
131 508 Microsoft Internet Informat 609 IIS|* 330 IBM Informix-4GL
132 550 Microsoft - IIS 6.0 Migration Tool 1 489 IIS|Easy Migration Tool (IEMT) 609 IIS|*
133 558 Infozip 6 85 Info-ZIP 677 Git
134 559 Infozip 85 Info-ZIP 677 Git
135 578 IMSVA 9.1 566 InterScan Messaging Security Virtual Appliance (IMSVA) 84 IMS DB
136 580 IMSVA 566 InterScan Messaging Security Virtual Appliance (IMSVA) 84 IMS DB
137 581 Java 1.8 584 Java|* 334 Java|Java Standard Edition (Java SE)
138 582 Java 7 584 Java|* 334 Java|Java Standard Edition (Java SE)
139 583 Java on Weblogic server 584 Java|* 600 Oracle WebLogic Server|*
140 584 Java5 584 Java|* 334 Java|Java Standard Edition (Java SE)
141 585 Java 6 584 Java|* 334 Java|Java Standard Edition (Java SE)
142 586 Java 6.0 584 Java|* 334 Java|Java Standard Edition (Java SE)
143 587 Java 7 Update 25 584 Java|* 334 Java|Java Standard Edition (Java SE)
144 589 Java (open source) 584 Java|* 397 Java|Servlet
145 590 Java 5 584 Java|* 334 Java|Java Standard Edition (Java SE)
146 591 Java 1.5 584 Java|* 334 Java|Java Standard Edition (Java SE)
147 593 Java 1.8.0_92 584 Java|* 334 Java|Java Standard Edition (Java SE)
148 594 Java 1.6 584 Java|* 334 Java|Java Standard Edition (Java SE)
149 595 J2EE 6 584 Java|* 333 Java|Java Enterprise Edition (Java EE)
150 596 Java (J2EE) 584 Java|* 333 Java|Java Enterprise Edition (Java EE)
151 598 JRE 506 Java Runtime Environment (JRE) 84 IMS DB
152 629 JEE 333 Java|Java Enterprise Edition (Java EE) 1 (E)JES
153 639 JSF 391 Java|JavaServer Faces (JSF) 334 Java|Java Standard Edition (Java SE)
154 643 JSP Scriptlets 336 Java|JavaServer Pages (JSP)|Scriptlets 335 Java|JavaServer Pages (JSP)
155 644 Java Scriplet 336 Java|JavaServer Pages (JSP)|Scriptlets 88 Ingres
156 645 Core 9.2.0.0 393 Java|JRuby Core 583 C++|*
157 647 Java RMI 396 Java|Remote Method Invocation (RMI) 584 Java|*
158 650 Java Servlets 397 Java|Servlet 453 Linux|Fedora
159 651 Java 6 Servlets 397 Java|Servlet 453 Linux|Fedora
160 652 J2EE Servlets 397 Java|Servlet 443 OS/2
161 653 Servlets 397 Java|Servlet 420 Cisco IOS
162 654 Servlets v2.3 397 Java|Servlet 370 Visual Basic
163 656 Spring BOOT 399 Java|Spring|Spring Boot 398 Java|Spring
164 657 Springboot 399 Java|Spring|Spring Boot 398 Java|Spring
165 661 javasript 589 JavaScript|* 335 Java|JavaServer Pages (JSP)
166 662 JS 589 JavaScript|* 507 Node.js
167 664 Java Script 589 JavaScript|* 584 Java|*
168 671 Sencha 4.2.0 409 JavaScript|Ext JS 589 JavaScript|*
169 674 jqueryui 412 JavaScript|Jquery|jQuery UI 411 JavaScript|JQuery
170 675 jquery-ui 412 JavaScript|Jquery|jQuery UI 411 JavaScript|JQuery
171 679 Scriptaculous 414 JavaScript|script.aculo.us 582 C#|*
172 684 EAP 268 JBoss|* 174 SAP ERP
173 685 JBOSS-EAP 268 JBoss|* 493 JBoss|Wildfly
174 686 JBoss Application Server 4 268 JBoss|* 493 JBoss|Wildfly
175 687 JBoss Application Server 7 268 JBoss|* 493 JBoss|Wildfly
176 688 JBoss Application Server 5 268 JBoss|* 493 JBoss|Wildfly
177 689 JBoss Application Server 268 JBoss|* 493 JBoss|Wildfly
178 690 Enterprise Application Platform 268 JBoss|* 670 EAServer
179 692 JBOSS 5.1.2 EAP 268 JBoss|* 493 JBoss|Wildfly
180 693 server: Jboss 268 JBoss|* 493 JBoss|Wildfly
181 694 JBOSS 6.3.2 EAP 268 JBoss|* 493 JBoss|Wildfly
182 695 JBoss EAP 4.3 268 JBoss|* 493 JBoss|Wildfly
183 700 Job Information Language 339 Job Information Language (JIL) 338 JCL
184 703 JoinIT by Acayosoft 91 joinIT 4 Adobe Acrobat Reader
185 704 Acayosoft JoinIT 91 joinIT 4 Adobe Acrobat Reader
186 705 JoinIT by Acayosoft v 9.0.8 91 joinIT 4 Adobe Acrobat Reader
187 706 LifeFlow Tool 92 LifeFlow 486 .NET Framework|Windows Workflow Foundation (WF)
188 707 Linux 2.6.32-696.28.1.el6.x86_64 576 Linux|* 437 Linux|zLinux
189 709 Linux 2.6.32-696.30.1.el6.x86_64 576 Linux|* 437 Linux|zLinux
190 710 Linux 2.6.9 576 Linux|* 437 Linux|zLinux
191 711 Linux 2.6.32-642.3.1.el6.x86_64 576 Linux|* 437 Linux|zLinux
192 712 Linux - 2.6.18-371.1.2.el5 576 Linux|* 437 Linux|zLinux
193 713 Linux 2.6.32-696.23.1.el6.x86_64 576 Linux|* 437 Linux|zLinux
194 749 Gaia Kernel version 2.7 428 Linux|Check Point 432 Linux|Oracle Linux
195 752 Gaia Kernel version 2.6 428 Linux|Check Point 432 Linux|Oracle Linux
196 766 OEL 432 Linux|Oracle Linux 449 Unix|HP-UX
197 778 Oracle Enterprise Server 7.5 432 Linux|Oracle Linux 134 Oracle Database
198 780 OEL6.7 - 3.8.13-68.3.4.el6uek.x86_64 432 Linux|Oracle Linux 449 Unix|HP-UX
199 792 VMware Photon 433 Linux|Photon OS 569 VMware Server
200 793 VMware Photon 1 433 Linux|Photon OS 569 VMware Server
201 809 Red Hat(Linux) 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
202 818 Redhat - Redhat Linux 7.2 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
203 819 Linux RH6 434 Linux|Red Hat Enterprise Linux 437 Linux|zLinux
204 865 Redhat - Redhat Linux 6.6 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
205 870 Redhat - RHEL 7.2 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
206 874 Red Hat Entreprise Linux 6.2 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
207 882 Redhat 6 64-Bit 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
208 893 RED HAT ADVANCED SERVER 5 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
209 910 redhat6.6 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
210 912 Redhat - Redhat Linux 6.3 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
211 913 Linux RH 434 Linux|Red Hat Enterprise Linux 437 Linux|zLinux
212 916 Redhat - Red Hat(Linux) 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
213 920 Linux RH7 434 Linux|Red Hat Enterprise Linux 437 Linux|zLinux
214 926 Red Hat V6 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
215 932 Linux RH5 434 Linux|Red Hat Enterprise Linux 437 Linux|zLinux
216 934 rehl5.9 434 Linux|Red Hat Enterprise Linux 43 DB2
217 964 Red Hat 6.6 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
218 979 red hat 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
219 991 Redhat 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
220 996 RedHat 7.3 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
221 998 LINUX RED HAT 5 EL 434 Linux|Red Hat Enterprise Linux 268 JBoss|*
222 1003 SUSE11 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
223 1006 Linux SuSE12 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
224 1011 SUSE10 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
225 1012 SUSE Linux 12 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
226 1017 SUSELinux Enterprise 11.x 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
227 1023 SUSE Linux 11 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
228 1024 SUSE Linux 11 SP3 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
229 1029 Linux SuSE11 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
230 1030 SUSE 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
231 1038 SuseLinux 435 Linux|SUSE Linux Enterprise Server 431 Linux|openSUSE
232 1051 domino8.5 270 Lotus Domino 93 Lotus Notes
233 1052 Domino 8.x 270 Lotus Domino 93 Lotus Notes
234 1054 Lucee 5.2.6.60 271 Lucee 375 Apache Lucene
235 1056 Darwin 438 macOS 117 Mozilla Firefox
236 1061 Memcache 98 Memcached 18 BMC Control-M
237 1062 ACCDB 99 Microsoft Access 525 Open Database Connectivity (ODBC)
238 1070 ConfigMgr 102 Microsoft Endpoint Configuration Manager (SCCM) 21 Business Intelligence and Reporting Tools (BIRT)
239 1080 FIM SQL Development Server 105 Microsoft Forefront Identity Manager (FIM) 572 Structured Query Language (SQL)
240 1082 Microsoft - Internet Explor 107 Microsoft Internet Explorer 356 Rexx
241 1084 Internet Explor 107 Microsoft Internet Explorer 356 Rexx
242 1090 SCEP for Linux 110 Microsoft System Center Endpoint Protection 437 Linux|zLinux
243 1094 SCEP for Mac 110 Microsoft System Center Endpoint Protection 438 macOS
244 1101 msdeploy 112 Microsoft Web Deploy 56 Greenplum DB
245 1106 WebPI 114 Microsoft Web Platform Installer 522 Application Web Server
246 1109 Web PI 114 Microsoft Web Platform Installer 531 Simple Object Access Protocol (SOAP)
247 1111 MDW Framework 115 Model Driven Workflow (MDW) 406 JavaScript|AngularJS
248 1115 Mango DB 116 MongoDB 43 DB2
249 1117 MangoDB 116 MongoDB 43 DB2
250 1125 O365 119 MS Office 365 424 IBM i
251 1141 MICROSOFT SQL SERVER 2012 DEVELOPER EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
252 1153 MICROSOFT SQL SERVER 2012 STANDARD EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
253 1154 MS SQL Server 2008 Developer 581 MS SQL Server|* 146 Oracle SQL Developer
254 1156 MICROSOFT SQL SERVER 2008 DEVELOPER EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
255 1167 MSSQL Database Server 581 MS SQL Server|* 122 MySQL
256 1173 MSSQL2008 581 MS SQL Server|* 122 MySQL
257 1192 Microsoft SQL Server Standard Edition 581 MS SQL Server|* 121 MS SQL Server Compact
258 1201 SQLServer 581 MS SQL Server|* 572 Structured Query Language (SQL)
259 1226 MICROSOFT SQL SERVER 2012 ENTERPRISE EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
260 1233 MICROSOFT SQL SERVER 2005 ENTERPRISE EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
261 1234 SQLSVR2008 581 MS SQL Server|* 352 PL/SQL
262 1235 MICROSOFT SQL SERVER 2008 ENTERPRISE EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
263 1239 MICROSOFT SQL SERVER 2008 STANDARD EDITION 581 MS SQL Server|* 121 MS SQL Server Compact
264 1244 MS SQL Server 2012 Developer 581 MS SQL Server|* 146 Oracle SQL Developer
265 1253 Microsoft - SQL Server Express LocalDB 2014 581 MS SQL Server|* 469 MS SQL Server|SQL Server Database Engine
266 1256 MSSQL 581 MS SQL Server|* 122 MySQL
267 1280 Microsoft - Microsoft SQL Server Analysis Services 2012 for Microsoft SQL Server 2012 Standard Edition 2012 468 MS SQL Server|SQL Server Analysis Services (SSAS) 581 MS SQL Server|*
268 1281 Microsoft - Microsoft SQL Server Analysis Services 2014 for Microsoft SQL Server 2014 Standard Edition 2014 468 MS SQL Server|SQL Server Analysis Services (SSAS) 581 MS SQL Server|*
269 1283 Microsoft - Microsoft SQL Server Analysis Services 2014 for Microsoft SQL Server 2014 Enterprise Edition 2014 468 MS SQL Server|SQL Server Analysis Services (SSAS) 581 MS SQL Server|*
270 1290 Microsoft - Microsoft SQL Server Integration Services 2014 for Microsoft SQL Server 2014 Enterprise Edition 2014 470 MS SQL Server|SQL Server Integration Services (SSIS) 581 MS SQL Server|*
271 1293 Microsoft - Microsoft SQL Server Integration Services 2014 for Microsoft SQL Server 2014 Standard Edition 2014 470 MS SQL Server|SQL Server Integration Services (SSIS) 581 MS SQL Server|*
272 1295 SQL Server Integration Services 470 MS SQL Server|SQL Server Integration Services (SSIS) 473 MS SQL Server|SQL Server Reporting Services (SSRS)
273 1316 ZOS Base 1.12 441 MVS|z/OS 437 Linux|zLinux
274 1335 NAS 272 Netscape Application Server (NAS) 443 OS/2
275 1337 NES 273 Netscape Enterprise Server (NES) 443 OS/2
276 1349 Node.js 0.10 (Linux) 507 Node.js 437 Linux|zLinux
277 1361 Node.js 4 (Linux) 507 Node.js 437 Linux|zLinux
278 1371 Symas OpenLDAP 126 OpenLDAP 178 SAP SQL Anywhere
279 1377 OAM 12c 129 Oracle Access Management 303 C
280 1378 ADF 12c 130 Oracle ADF 343 Objective C
281 1381 OHS 610 Oracle Application Server|* 122 MySQL
282 1383 Oracle HTTP Server powered by Apache 610 Oracle Application Server|* 259 Apache HTTP Server
283 1384 j2eeoracleca 610 Oracle Application Server|* 453 Linux|Fedora
284 1385 Oracle HTTP 610 Oracle Application Server|* 134 Oracle Database
285 1389 9i AS server 610 Oracle Application Server|* 227 Virtual I/O Server
286 1391 Oracle Application R12.1.3 610 Oracle Application Server|* 134 Oracle Database
287 1394 Weblogic BI Publisher 132 Oracle BI Publisher 600 Oracle WebLogic Server|*
288 1396 OBI 133 Oracle Business Intelligence 343 Objective C
289 1397 OBIEE 133 Oracle Business Intelligence 343 Objective C
290 1398 OBI Reporting 133 Oracle Business Intelligence 343 Objective C
291 1401 Oracle 12.2 Client 134 Oracle Database 610 Oracle Application Server|*
292 1406 Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 134 Oracle Database 610 Oracle Application Server|*
293 1407 Oracle 11.2 (Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit) RAC 134 Oracle Database 610 Oracle Application Server|*
294 1415 Oracle 11 on AIX 134 Oracle Database 445 Unix|AIX
295 1416 Oracle Database 10g Enterprise Edition Release 10.1.0.4.0 - 64bit 134 Oracle Database 610 Oracle Application Server|*
296 1431 Oracle Database 10g Release 10.2.0.4.0 - 64bit Production 134 Oracle Database 298 Oracle Exadata
297 1432 Oarcle 11G 134 Oracle Database 218 TIBCO InConcert
298 1443 DB - Oracle inbuilt 134 Oracle Database 158 Powerbuilder
299 1460 Oracle Server 134 Oracle Database 610 Oracle Application Server|*
300 1475 Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 - 64bit Production 134 Oracle Database 610 Oracle Application Server|*
301 1480 Oracle 12C on linux 134 Oracle Database 303 C
302 1484 Oracle9i Enterprise Edition Release 9.2.0.5.0 134 Oracle Database 610 Oracle Application Server|*
303 1486 Oracle 11g on linux 134 Oracle Database 432 Linux|Oracle Linux
304 1487 Oracle 11gEssbase 134 Oracle Database 298 Oracle Exadata
305 1490 JServer Release 9.2.0.5.0 474 Oracle Database|Jserver 335 Java|JavaServer Pages (JSP)
306 1492 Designer 6i 135 Oracle Designer 516 Compopent Object Model (COM)
307 1493 Enterprise Manager 12.2.1.1 136 Oracle Enterprise Manager 427 Linux|CentOS
308 1494 Enterprise Manager 12.2.1.2 136 Oracle Enterprise Manager 427 Linux|CentOS
309 1495 Enterprise Manager 11.1.1.7 136 Oracle Enterprise Manager 427 Linux|CentOS
310 1501 Oracle, Nets 140 Oracle Net Services 273 Netscape Enterprise Server (NES)
311 1502 Oracle RAC 141 Oracle Real Application Clusters (RAC) 134 Oracle Database
312 1504 ORPOS 13.3.3 142 Oracle Retail Point-of-Service 609 IIS|*
313 1505 ORPOS 13.3.5 142 Oracle Retail Point-of-Service 609 IIS|*
314 1506 ORPOS 13.3.4 142 Oracle Retail Point-of-Service 609 IIS|*
315 1509 OSB Servers 143 Oracle Service Bus 443 OS/2
316 1514 Oracle TT 147 Oracle TimesTen In-Memory Database 134 Oracle Database
317 1517 OWB 10g 148 Oracle Warehouse Builder (OWB) 300 AWK
318 1524 Clascal 346 Pascal|Object Pascal 307 Cascading Style Sheets (CSS)
319 1526 Oracle-HR-9.2 151 PeopleSoft 134 Oracle Database
320 1529 ActiveState Tool Corp. - ActivePerl 5.12 348 Perl|ActivePerl 500 ActiveX
321 1530 ActiveState Tool Corp. - ActivePerl 5.8 348 Perl|ActivePerl 500 ActiveX
322 1531 ORAPERL 417 Perl|Oraperl 242 WinRAR
323 1532 REX 349 Perl|Rex 356 Rexx
324 1536 TCServer V6 277 Pivotal tc Server 365 TCL
325 1537 IBM PKWARE PKZip 2 155 PKZIP 387 Java|IBM SDK
326 1541 PLQSL 352 PL/SQL 351 PL/I
327 1542 Oracle - SQL 352 PL/SQL 581 MS SQL Server|*
328 1544 Oracle SQL 352 PL/SQL 134 Oracle Database
329 1545 PLSQL; 352 PL/SQL 351 PL/I
330 1547 Oracle PLSQL 352 PL/SQL 351 PL/I
331 1548 plsql 352 PL/SQL 351 PL/I
332 1551 Projectplace 156 Planview 21 Business Intelligence and Reporting Tools (BIRT)
333 1558 Power Builder 158 Powerbuilder 151 PeopleSoft
334 1560 Power Builder 6.5 158 Powerbuilder 27 Chef Automate
335 1565 ProjectWise Oracle Server 161 ProjectWise 162 ProjectWise Web Server
336 1576 RMQ 165 RabbitMQ 355 R
337 1579 Clearquest 167 Rational ClearQuest 455 Clarify|Clear Basic
338 1581 Remedy ARS 169 Remedy 322 Fortran
339 1584 RightFax client 10 171 RightFax 118 MQ Client
340 1585 SOQL 359 Salesforce Object Query Language (SOQL) 621 ArangoDB
341 1587 SAP Business Objects 173 SAP BusinessObjects BI server 177 SAP NetWeaver Business Warehouse
342 1588 Business Objects 12 173 SAP BusinessObjects BI server 488 ActiveX|ADO
343 1590 SAP BI 4.2 Sp5 173 SAP BusinessObjects BI server 174 SAP ERP
344 1593 SAP HANA ON SUSEOracle 11g on Linux 175 SAP HANA DB 435 Linux|SUSE Linux Enterprise Server
345 1596 NetWeaver 279 SAP NetWeaver App Server 431 Linux|openSUSE
346 1605 SCSS 361 Sass 102 Microsoft Endpoint Configuration Manager (SCCM)
347 1606 Scalla 362 Scala 664 Forte
348 1609 Microsoft SPS 2010 603 SharePoint|* 577 MVS|*
349 1613 SQL Server SP2013 Database Server 603 SharePoint|* 581 MS SQL Server|*
350 1615 Siebel IP 2015 182 Siebel 583 C++|*
351 1616 Siebel 7.8.2.16 182 Siebel 43 DB2
352 1617 Siebel CRM 182 Siebel 583 C++|*
353 1619 Techsmith Corporation - SnagIt 8 184 SnagIt 183 SNA Manager
354 1620 Solid development server 185 solidDB 600 Oracle WebLogic Server|*
355 1622 Sixty-Five Software - SpaceMonger 1.4 187 SpaceMonger 296 Intel Xeon Processor
356 1623 SQLPlus 478 Oracle Database|SQL*Plus 572 Structured Query Language (SQL)
357 1625 SQLIO 1.0 189 SQLIO 178 SAP SQL Anywhere
358 1630 SunOne 281 Oracle iPlanet Web Server 448 Unix|BSD|SunOS
359 1637 SAP - Sybase Central 4.3 479 Sybase SQL Server|Sybase Central 190 Sybase SQL Server
360 1639 Sysncsort 191 Syncsort 178 SAP SQL Anywhere
361 1640 syncsort 191 Syncsort 98 Memcached
362 1641 Sysinternals LLC - AccessEnum 1 1 194 Sysinternal Tools|AccessEnum 124 Nexus Repository OSS
363 1642 Sysinternals LLC - ClockRes 2 195 Sysinternal Tools|ClockRes 374 Xbase++
364 1643 Sysinternals LLC - Coreinfo 3.21 196 Sysinternal Tools|Coreinfo 670 EAServer
365 1644 Sysinternals LLC - DiskExt 1.1 197 Sysinternal Tools|DiskExt 374 Xbase++
366 1645 Sysinternals LLC - DiskMon 2.01 198 Sysinternal Tools|DiskMon 670 EAServer
367 1647 Sysinternals LLC - Junction 1.6 200 Sysinternal Tools|Junction 374 Xbase++
368 1648 Sysinternals LLC - LDMDump 1.02 201 Sysinternal Tools|LDMDump 178 SAP SQL Anywhere
369 1649 Sysinternals LLC - LoadOrder 1 202 Sysinternal Tools|LoadOrder 374 Xbase++
370 1650 Sysinternals LLC - PipeList 1.01 203 Sysinternal Tools|PipeList 670 EAServer
371 1651 Sysinternals LLC - Process Explorer 16.5 204 Sysinternal Tools|Process Explorer 464 Microsoft Exchange Server|Veeam Explorer
372 1652 Sysinternals LLC - PsKill 1.15 205 Sysinternal Tools|PsKill 151 PeopleSoft
373 1653 Sysinternals LLC - PsPasswd 1.23 206 Sysinternal Tools|PsPasswd 231 VMware vCenter
374 1654 Sysinternals LLC - SDelete 1.61 207 Sysinternal Tools|SDelete 670 EAServer
375 1655 Sysinternals LLC - ShareEnum 1.6 208 Sysinternal Tools|ShareEnum 603 SharePoint|*
376 1656 Sysinternals LLC - Sync 2.2 209 Sysinternal Tools|Sync 374 Xbase++
377 1657 Sysinternals LLC - Sysinternals TCPView 3.5 210 Sysinternal Tools|TCPView 365 TCL
378 1658 Sysinternals LLC - VMMap 3.11 211 Sysinternal Tools|VMMap 176 SAP MaxDB
379 1659 Sysinternals LLC - Whois 1.11 212 Sysinternal Tools|Whois 178 SAP SQL Anywhere
380 1664 TERADATA QUERY SCHEDULER SERVER VERSION 15 216 Teradata QS Server 215 Teradata
381 1667 BusinessWorks 217 TIBCO Business Works (BW) 111 Microsoft Visual Studio
382 1668 Tibco-IM 481 TIBCO Business Works (BW)|Integration Manager 219 TIBCO Rendezvous
383 1669 Tibco Integration Manager 481 TIBCO Business Works (BW)|Integration Manager 219 TIBCO Rendezvous
384 1674 TSQL 366 Transact-SQL 621 ArangoDB
385 1675 Trasact SQL 366 Transact-SQL 352 PL/SQL
386 1746 Solaris 11.2 SPARC 448 Unix|BSD|SunOS 375 Apache Lucene
387 1747 Solaris UNIX 448 Unix|BSD|SunOS 578 Unix|*
388 1748 Unix Servers (Solaris 448 Unix|BSD|SunOS 578 Unix|*
389 1749 Oracle Solaris 11.3 SPARC 448 Unix|BSD|SunOS 375 Apache Lucene
390 1753 Solaris 5.10 (Generic_150400-61) 448 Unix|BSD|SunOS 521 Electronic Data Interchange (EDI)
391 1754 Solaris 5.10 (Generic_150400-62) 448 Unix|BSD|SunOS 521 Electronic Data Interchange (EDI)
392 1756 Solaris 5.10 (Generic_150400-55) 448 Unix|BSD|SunOS 521 Electronic Data Interchange (EDI)
393 1760 Oracle Solaris 448 Unix|BSD|SunOS 134 Oracle Database
394 1762 Solaris 1 (SPARC) 448 Unix|BSD|SunOS 375 Apache Lucene
395 1765 SunSolaris 10.0 448 Unix|BSD|SunOS 430 Linux|Junos OS
396 1771 Oracle Solaris 10 448 Unix|BSD|SunOS 134 Oracle Database
397 1800 VIO 2.2.0.10 227 Virtual I/O Server 159 Primavera P6
398 1801 VIOS 227 Virtual I/O Server 443 OS/2
399 1802 visibroker 228 Visibroker 420 Cisco IOS
400 1803 VB6 370 Visual Basic 368 VB.NET
401 1804 VB 6.0 370 Visual Basic 368 VB.NET
402 1805 visualbasic 370 Visual Basic 306 C++|Visual C++
403 1808 Visual Basic 6.0 370 Visual Basic 368 VB.NET
404 1811 VBA 371 Visual Basic for Applications (VBA) 370 Visual Basic
405 1812 Access VB 371 Visual Basic for Applications (VBA) 99 Microsoft Access
406 1813 vfoxpro 372 Visual FoxPro 117 Mozilla Firefox
407 1827 VMware Appliance 569 VMware Server 559 Virtual Appliance
408 1828 VSX 229 VMware Solution Exchange Marketplace (VSX) 111 Microsoft Visual Studio
409 1830 VMware - VMware Tools 10.2 230 VMware Tools 569 VMware Server
410 1832 VXML 373 VoiceXML 316 eXtensible HyperText Markup Language (XHTML)
411 1833 Web Focus 232 WebFOCUS 321 FOCUS
412 1834 FOCEXEC 232 WebFOCUS 495 Oracle WebCenter Content Server|Idoc Script
413 1836 WLI 8 233 WebLogic Integration 442 OpenVMS
414 1842 IBM WEBSPHERE APPLICATION SERVER VERSION 6.1.0 284 Websphere Application Server (WAS) 285 WebSphere Liberty
415 1848 IBM WebSphere Application Server Network Deployment, 8.0.0.5 284 Websphere Application Server (WAS) 285 WebSphere Liberty
416 1850 IBM WebSphere Application Server Network Deployment 7 284 Websphere Application Server (WAS) 285 WebSphere Liberty
417 1858 IBM WebSphere 8.5 284 Websphere Application Server (WAS) 285 WebSphere Liberty
418 1861 IBM - WebSphere Application Server - Base 8.5 284 Websphere Application Server (WAS) 285 WebSphere Liberty
419 1865 Websphere AS (JVM) 284 Websphere Application Server (WAS) 285 WebSphere Liberty
420 1872 IBM WebSphere 284 Websphere Application Server (WAS) 285 WebSphere Liberty
421 1875 IBM WebSphere Application Server 8.5 284 Websphere Application Server (WAS) 285 WebSphere Liberty
422 1877 IBM WebSphere Application 284 Websphere Application Server (WAS) 285 WebSphere Liberty
423 1878 WAS 6.x 284 Websphere Application Server (WAS) 521 Electronic Data Interchange (EDI)
424 1880 IBM OpenStack Liberty 285 WebSphere Liberty 431 Linux|openSUSE
425 1882 Open Liberty 285 WebSphere Liberty 397 Java|Servlet
426 1883 IBM Open Liberty 285 WebSphere Liberty 62 IBM BigFix Platform
427 1887 WAS Liberty 285 WebSphere Liberty 397 Java|Servlet
428 1889 OpenStack Liberty 285 WebSphere Liberty 431 Linux|openSUSE
429 1891 WMB 6.1 235 WebSphere Message Broker 486 .NET Framework|Windows Workflow Foundation (WF)
430 1892 WebSphere Message Broker v6.0 235 WebSphere Message Broker 285 WebSphere Liberty
431 1899 WebSphere Portal Extend Limited Use 6.1 286 WebSphere Portal Server 285 WebSphere Liberty
432 1901 Windchill 11.1 237 Windchill 17 Bluebeam|Bluebeam Q
433 1908 Window 580 Windows|* 637 Microsoft Azure
434 1914 Windows Terminal Server 239 Windows Terminal Server (WTS) 452 Windows|Windows Server
435 1915 Windows 7 Standard 451 Windows|Windows Desktop 580 Windows|*
436 1916 WINDOWS 10 SERVER STANDARD EDITION X64 451 Windows|Windows Desktop 452 Windows|Windows Server
437 1917 Microsoft Windows 7 (64-bit) 451 Windows|Windows Desktop 580 Windows|*
438 1918 Microsoft Windows XP Professional (32-bit) 451 Windows|Windows Desktop 580 Windows|*
439 1919 Windows 7 Professional x64 451 Windows|Windows Desktop 580 Windows|*
440 1920 Microsoft Microsoft Windows Entreprise 451 Windows|Windows Desktop 580 Windows|*
441 1921 Microsoft Windows 2000 451 Windows|Windows Desktop 580 Windows|*
442 1922 Microsoft Windows 10 451 Windows|Windows Desktop 580 Windows|*
443 1923 MS Microsoft Windows 7 451 Windows|Windows Desktop 580 Windows|*
444 1924 Microsoft Windows 7 Professional 451 Windows|Windows Desktop 580 Windows|*
445 1925 Microsoft Microsoft Windows 7 Enterprise 451 Windows|Windows Desktop 580 Windows|*
446 1926 Microsoft Windows 10 Enterprise 451 Windows|Windows Desktop 580 Windows|*
447 1927 Win Desktop 451 Windows|Windows Desktop 560 Webtop
448 1928 Windows 10 Pro 451 Windows|Windows Desktop 580 Windows|*
449 1929 Windows 10 451 Windows|Windows Desktop 580 Windows|*
450 1930 Windows 7 Ultimate 451 Windows|Windows Desktop 580 Windows|*
451 1931 Microsoft Windows 8 (64-bit) 451 Windows|Windows Desktop 580 Windows|*
452 1932 Microsoft Windows XP 451 Windows|Windows Desktop 580 Windows|*
453 1933 Windows 10 Enterprise 451 Windows|Windows Desktop 580 Windows|*
454 1934 Windows XP 451 Windows|Windows Desktop 580 Windows|*
455 1935 Windows 10 Professional 451 Windows|Windows Desktop 580 Windows|*
456 1936 Windows 7 451 Windows|Windows Desktop 580 Windows|*
457 1937 Microsoft Windows 10 (64-bit) 451 Windows|Windows Desktop 580 Windows|*
458 1938 Win 7 451 Windows|Windows Desktop 333 Java|Java Enterprise Edition (Java EE)
459 1939 windowsxp 451 Windows|Windows Desktop 580 Windows|*
460 1940 Microsoft Windows Unknown 451 Windows|Windows Desktop 580 Windows|*
461 1941 Windows 7 Enterprise 451 Windows|Windows Desktop 580 Windows|*
462 1942 Windows XP Professional 451 Windows|Windows Desktop 580 Windows|*
463 1943 Windows 7 Professional 451 Windows|Windows Desktop 580 Windows|*
464 1944 Window XP 451 Windows|Windows Desktop 580 Windows|*
465 1945 Microsoft Windows 7 Enterprise 451 Windows|Windows Desktop 580 Windows|*
466 1946 Microsoft Windows 7 - SOE 451 Windows|Windows Desktop 580 Windows|*
467 1947 Windows 7 Enterprise Edition 451 Windows|Windows Desktop 452 Windows|Windows Server
468 1948 Windows 8 451 Windows|Windows Desktop 580 Windows|*
469 1949 Microsoft Windows 7 451 Windows|Windows Desktop 580 Windows|*
470 1950 Microsoft Windows 7 (32-bit) 451 Windows|Windows Desktop 580 Windows|*
471 1951 Windows Embedded Standard 7 451 Windows|Windows Desktop 580 Windows|*
472 1952 Win10 451 Windows|Windows Desktop 333 Java|Java Enterprise Edition (Java EE)
473 1953 Windows 2003 451 Windows|Windows Desktop 580 Windows|*
474 1955 Windows 2003 Standard 452 Windows|Windows Server 580 Windows|*
475 1956 Windows 2008 Enterprise R2 x64 452 Windows|Windows Server 580 Windows|*
476 1960 WINDOWS 2008R2 452 Windows|Windows Server 580 Windows|*
477 1961 Microsoft Windows Server 2008 Standard Editio 452 Windows|Windows Server 121 MS SQL Server Compact
478 1962 MICROSOFT WINDOWS NT 2003 452 Windows|Windows Server 580 Windows|*
479 1967 Microsoft Microsoft Windows Server 2016 Datacenter 452 Windows|Windows Server 276 Oracle WebCenter Content Server
480 1979 Windows 2008 Enterprise 32-bit 452 Windows|Windows Server 580 Windows|*
481 1982 Windows 2003 R2 452 Windows|Windows Server 580 Windows|*
482 1983 Windows 2008 R2 Enterprise 64 Bit 452 Windows|Windows Server 580 Windows|*
483 1988 Windows 2008 R2 452 Windows|Windows Server 580 Windows|*
484 1989 Windows 2012 Standard 452 Windows|Windows Server 580 Windows|*
485 1992 Windows 2008 R2 Standard 6.1.7601 Service Pack 1 452 Windows|Windows Server 580 Windows|*
486 1994 Windows 2008 Standard x64 452 Windows|Windows Server 580 Windows|*
487 1998 Windows 2012 R2 Standard 64-Bit 452 Windows|Windows Server 580 Windows|*
488 2007 w2k12 452 Windows|Windows Server 582 C#|*
489 2008 WINDOWS 2013 452 Windows|Windows Server 580 Windows|*
490 2009 WINDOWS 2016 SE 64 BIT 452 Windows|Windows Server 580 Windows|*
491 2011 Microsoft - Windows 2012 452 Windows|Windows Server 580 Windows|*
492 2019 MICROSOFT WINDOWS 2008 TPM 452 Windows|Windows Server 580 Windows|*
493 2021 MICROSOFT WINDOWS STD 2008 452 Windows|Windows Server 580 Windows|*
494 2025 Windows 2008 R2 Standard 64 Bit 452 Windows|Windows Server 580 Windows|*
495 2028 MICROSOFT WINDOWS STD 2008 TPM 452 Windows|Windows Server 580 Windows|*
496 2030 Windows 2012 64 Bit 452 Windows|Windows Server 580 Windows|*
497 2031 MICROSOFT WINDOWS NT 2003 ENT 452 Windows|Windows Server 580 Windows|*
498 2034 MICROSOFT WINDOWS 2012 452 Windows|Windows Server 580 Windows|*
499 2036 Windows 2003 Standard5.2.3790 452 Windows|Windows Server 580 Windows|*
500 2040 Windows 2012 R 452 Windows|Windows Server 580 Windows|*
501 2044 Windows 2008 Enterprise 32 Bit 452 Windows|Windows Server 580 Windows|*
502 2045 MICROSOFT WINDOWS 2008 ENT 452 Windows|Windows Server 580 Windows|*
503 2047 Windows 2012 R2 Standard 6.3.9600 452 Windows|Windows Server 580 Windows|*
504 2053 Windows 2016 Datacenter 452 Windows|Windows Server 276 Oracle WebCenter Content Server
505 2055 Microsoft Windows Server 2016 Datacenter 452 Windows|Windows Server 276 Oracle WebCenter Content Server
506 2061 Windows 2016 Datacenter10.0.14393 452 Windows|Windows Server 637 Microsoft Azure
507 2065 windows6.3.9600 452 Windows|Windows Server 580 Windows|*
508 2066 Windows 2012 R2 Standard 64 Bit 452 Windows|Windows Server 580 Windows|*
509 2069 Windows 2008 Enterprise 452 Windows|Windows Server 580 Windows|*
510 2080 Windows 2008 Standard without Hyper-V6.0.6003 452 Windows|Windows Server 580 Windows|*
511 2084 Windows 2012 R2 Datacenter 452 Windows|Windows Server 110 Microsoft System Center Endpoint Protection
512 2089 Windows 2008 Standard 64-bit 452 Windows|Windows Server 580 Windows|*
513 2096 Windows 2000 452 Windows|Windows Server 580 Windows|*
514 2097 W2K8R2 Standard 64 BIT 452 Windows|Windows Server 303 C
515 2099 Windows 2008 Standard6.0.6003 452 Windows|Windows Server 580 Windows|*
516 2100 Windows2008 R2 Enterprise 64bit 452 Windows|Windows Server 580 Windows|*
517 2105 Win2008R2 452 Windows|Windows Server 355 R
518 2107 Windows 2008 Standard 64 Bit 452 Windows|Windows Server 580 Windows|*
519 2109 Windows Server 2003 Appliance 452 Windows|Windows Server 559 Virtual Appliance
520 2111 Windows 2008 ENT R2 (64 bits) 452 Windows|Windows Server 355 R
521 2114 WIN2008R2 6.1.7601 452 Windows|Windows Server 355 R
522 2116 microsoft windows std 2012 tpm 452 Windows|Windows Server 580 Windows|*
523 2118 microsoft windows 2008 452 Windows|Windows Server 580 Windows|*
524 2120 Windows 2008 Standard 32 Bit 452 Windows|Windows Server 580 Windows|*
525 2121 Microsoft Windows 2008 R2 Standard 452 Windows|Windows Server 580 Windows|*
526 2126 Window2008 R2 452 Windows|Windows Server 355 R
527 2130 Windows 2008 Standard 452 Windows|Windows Server 580 Windows|*
528 2134 WS03 452 Windows|Windows Server 239 Windows Terminal Server (WTS)
529 2136 Windows 2008 Enterprise x64 452 Windows|Windows Server 580 Windows|*
530 2141 Windows 2008 R2 Enterprise 452 Windows|Windows Server 580 Windows|*
531 2142 Windows Server 2003 Std 32-bit 452 Windows|Windows Server 580 Windows|*
532 2143 Windows 2008 R2 Standard 64bit 452 Windows|Windows Server 580 Windows|*
533 2146 Microsoft Windows 2003 R2 Standard 452 Windows|Windows Server 580 Windows|*
534 2148 MICROSOFT WINDOWS NT 2003 TPM 452 Windows|Windows Server 580 Windows|*
535 2149 Win Server 2008 452 Windows|Windows Server 569 VMware Server
536 2150 Windows 2003 R2 Standard 64 Bit 452 Windows|Windows Server 580 Windows|*
537 2152 WIN2014 452 Windows|Windows Server 333 Java|Java Enterprise Edition (Java EE)
538 2156 Win 2012 R2 452 Windows|Windows Server 355 R
539 2160 Win Server 452 Windows|Windows Server 12 Apache Subversion
540 2161 Windows 2008 Standard R2 x64 452 Windows|Windows Server 580 Windows|*
541 2163 Windows server 2008 Dual processor Intel Xeon x5660 @2.80 GHz 6196 MB memory installed 452 Windows|Windows Server 296 Intel Xeon Processor
542 2164 Windows2012 452 Windows|Windows Server 580 Windows|*
543 2165 Windows 2008 R2 Standard6.1.7601 452 Windows|Windows Server 580 Windows|*
544 2166 Windows 2016 452 Windows|Windows Server 580 Windows|*
545 2167 Windows 2008 R2 Standard 452 Windows|Windows Server 580 Windows|*
546 2179 Windows Server 2003 Std 64-bit 452 Windows|Windows Server 580 Windows|*
547 2180 Windows 2012 R2 452 Windows|Windows Server 580 Windows|*
548 2181 Wintel 452 Windows|Windows Server 461 IBM Tivoli Storage Manager|TSM Client
549 2191 Windows 2003 Enterprise5.2.3790 452 Windows|Windows Server 580 Windows|*
550 2192 WINDOWS 2012 452 Windows|Windows Server 580 Windows|*
551 2193 Windows 2008 R2 OS 452 Windows|Windows Server 580 Windows|*
552 2196 Windows 2003 Standard R2 452 Windows|Windows Server 580 Windows|*
553 2197 Windows 2008 R2 Enterprise6.1.7601 452 Windows|Windows Server 580 Windows|*
554 2198 Windows 2003 Standard 32 Bit 452 Windows|Windows Server 580 Windows|*
555 2199 WINDOWS SERVER 2003 APPLIANCE 5.2 452 Windows|Windows Server 559 Virtual Appliance
556 2201 WS08R2 452 Windows|Windows Server 355 R
557 2204 Windows 2008 Enterprise 64 Bit 452 Windows|Windows Server 580 Windows|*
558 2213 w2k8r2sp1 452 Windows|Windows Server 355 R
559 2217 Win 2003 452 Windows|Windows Server 333 Java|Java Enterprise Edition (Java EE)
560 2222 Windows 2012 R2 Standard 452 Windows|Windows Server 580 Windows|*
561 2226 Windows 2008 R2 Standard 64-bit 452 Windows|Windows Server 580 Windows|*
562 2228 Windows 2003 Enterprise 32-bit 452 Windows|Windows Server 580 Windows|*
563 2230 Windows 2012 Storage R2 452 Windows|Windows Server 580 Windows|*
564 2231 Windows server 2008 Dual processor Intel Xeon x5660 @2.80 GHz 4096 MB memory installed 452 Windows|Windows Server 296 Intel Xeon Processor
565 2235 MICROSOFT WINDOWS NT 2003 ENT TPM 452 Windows|Windows Server 239 Windows Terminal Server (WTS)
566 2237 Windows 2016 Standard10.0.14393 452 Windows|Windows Server 580 Windows|*
567 2240 MICROSOFT WINDOWS 2003 452 Windows|Windows Server 580 Windows|*
568 2242 Windows 2012 Standard R2 452 Windows|Windows Server 580 Windows|*
569 2246 Win Server 2008 R2 452 Windows|Windows Server 355 R
570 2248 MICROSOFT WINDOWS STD 2012 TPM 452 Windows|Windows Server 580 Windows|*
571 2249 Windows 2003 Enterprise 32 Bit 452 Windows|Windows Server 580 Windows|*
572 2250 Windows 2008 Enterprise R2 452 Windows|Windows Server 580 Windows|*
573 2251 Windows 2008 452 Windows|Windows Server 580 Windows|*
574 2252 Microsoft Microsoft Windows 2008 R2 452 Windows|Windows Server 580 Windows|*
575 2257 Win Server 2012 452 Windows|Windows Server 569 VMware Server
576 2258 Windows 2016 Standard 452 Windows|Windows Server 580 Windows|*
577 2264 Windows 2008 Enterprise 64-bit 452 Windows|Windows Server 580 Windows|*
578 2267 Windows 2003 Standard 5.2.3790 Service Pack 2 452 Windows|Windows Server 580 Windows|*
579 2268 Windows 2012 Standard6.2.9200 452 Windows|Windows Server 580 Windows|*
580 2269 MICROSOFT WINDOWS 2016 TPM 452 Windows|Windows Server 580 Windows|*
581 2272 Windows 2003 Enterprise 452 Windows|Windows Server 580 Windows|*
582 2275 Windows 2008 R2 Enterprise 64-bit 452 Windows|Windows Server 580 Windows|*
583 2277 Windows 2012 R2 Standard6.3.9600 452 Windows|Windows Server 580 Windows|*
584 2286 Windows 2008 Standard R2 452 Windows|Windows Server 580 Windows|*
585 2287 MicrosoftWindows Server 2008 R2 (64-bit) 452 Windows|Windows Server 443 OS/2
586 2288 windows6.3 452 Windows|Windows Server 580 Windows|*
587 2290 Windows 2016 64 Bit 452 Windows|Windows Server 580 Windows|*
588 2296 Windows 2008 Enterprise6.0.6003 452 Windows|Windows Server 580 Windows|*
589 2301 Win 2012 452 Windows|Windows Server 333 Java|Java Enterprise Edition (Java EE)
590 2302 Win2012 452 Windows|Windows Server 333 Java|Java Enterprise Edition (Java EE)
591 2303 Win2012R2 452 Windows|Windows Server 355 R
592 2305 win2008 452 Windows|Windows Server 333 Java|Java Enterprise Edition (Java EE)
593 2306 Windows 2003 Standard x64 452 Windows|Windows Server 580 Windows|*
594 2315 WINDOWS 2016 STANDARD EDITION 452 Windows|Windows Server 580 Windows|*
595 2325 WinSCP.net - WinSCP 5.11 243 WinSCP 178 SAP SQL Anywhere
596 2332 Zerto Vritual Appliance 249 Zerto Virtual Replication 559 Virtual Appliance
597 2333 Oracle RTD 289 Oracle Real-Time Decisions (RTD) 134 Oracle Database
598 2338 OMNIbus 251 Tivoli Netcool/OMNIbus 582 C#|*
599 2347 ALM 511 Application Lifecycle Management (ALM) 421 DART
600 2349 BMS 513 Batch Management Software (BMS) 442 OpenVMS
601 2354 COM 516 Compopent Object Model (COM) 661 COM+
602 2357 CORBA Interface Definition Language 518 CORBA Interface Definition Language (CORBA IDL) 517 Common Object Request Broker Architecture (CORBA)
603 2359 Data Control Language 519 Data Control Language (DCL) 329 IBM i Control Language (CL)
604 2361 Database 520 Database (DB) 43 DB2
605 2362 DB 520 Database (DB) 43 DB2
606 2365 Electronic Data Interchange 521 Electronic Data Interchange (EDI) 104 Microsoft Exchange Server
607 2369 JDOM 523 Java-based Document Object Model for XML (JDOM) 84 IMS DB
608 2381 Simple Object Access Protocol 531 Simple Object Access Protocol (SOAP) 547 Internet Message Access Protocol (IMAP)
609 2383 SQL 572 Structured Query Language (SQL) 581 MS SQL Server|*
610 2386 DPE 538 Device Provisioning Engines (DPE) 661 COM+
611 2388 ESB 540 Enterprise Service Bus(ESB) 370 Visual Basic
612 2395 MES 553 Manufacturing Execution System (MES) 623 Amazon S3
613 2401 Z/Virtual System Environment 591 z/VSE 441 MVS|z/OS
614 2403 DOS/VSE 591 z/VSE 597 DOS/360
615 2404 Microsoft Disk Operating System 593 MS-DOS 443 OS/2
616 2407 VME/B 595 VME 368 VB.NET
617 2408 Virtual Machine Environment 595 VME 111 Microsoft Visual Studio
618 2409 VME 2900 595 VME 107 Microsoft Internet Explorer
619 2410 OpenVME 595 VME 442 OpenVMS
620 2411 Disk Operating System/360 597 DOS/360 443 OS/2
621 2413 Transaction Processing Facility 598 z/TPF 572 Structured Query Language (SQL)
622 2419 NPL 653 Natural Programming Language 342 Niakwa Programming Language (NPL)
623 2426 IDMS/DB Data Manipulation Language 668 IDMS DML 312 Data Language Interface (DL/I)
624 2433 Basic Mapping Supprt 689 BMS Map 21 Business Intelligence and Reporting Tools (BIRT)
625 2434 DB/400 690 DB400 43 DB2
626 2435 IBM ISAM 693 ISAM 73 IBM Operational Decision Manager (ODM)

14
zero_shot/t5.py → zero_shot/flan-t5.py
View File

@ -32,21 +32,25 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
def generate_acronym(text):
# Define prompt
prompt = f"Answer concisely: make a possible acronym from the following: '{text}'"
# prompt = f"Imagine you are a diverse database. Given the following: '{text}', please suggest to me 5 possible variations. Give 5."
prompt = f"Give me a list of 10 historical product names related to: '{text}'. Format the output in a list, like this 1. Item, 2. Item, 3. ..."
# Generate acronym
inputs = tokenizer(prompt, return_tensors="pt")
inputs = inputs.to("cuda")
outputs = model.generate(
inputs["input_ids"],
max_length=100,
no_repeat_ngram_size=3)
max_length=200,
do_sample=True,
top_k=50,
temperature=0.8)
# no_repeat_ngram_size=3)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
# %%
# Example usage
# text = "Advanced Data Analytics Platform"
text = "red hat enterprise linux"
text = "windows desktop"
acronym = generate_acronym(text)
print(f"Acronym: {acronym}")
print(f"Generation: {acronym}")
# %%