Hott et al., 2023 - Google Patents
Evaluating contextualized embeddings for topic modeling in public bidding domainHott et al., 2023
- Document ID
- 17855736322259711929
- Author
- Hott H
- Silva M
- Oliveira G
- Brandão M
- Lacerda A
- Pappa G
- Publication year
- Publication venue
- Brazilian Conference on Intelligent Systems
External Links
Snippet
Public procurement plays a crucial role in government operations by acquiring goods and services through competitive bidding processes. However, the increasing volume of procurement data has made manual analysis impractical and time-consuming. Therefore …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/3066—Query translation
- G06F17/30669—Translation of the query language, e.g. Chinese to English
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
- G06F17/30675—Query execution
- G06F17/30684—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/30707—Clustering or classification into predefined classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/28—Processing or translating of natural language
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Arulmurugan et al. | RETRACTED ARTICLE: Classification of sentence level sentiment analysis using cloud machine learning techniques | |
Giatsoglou et al. | Sentiment analysis leveraging emotions and word embeddings | |
Wu et al. | Operationalizing regulatory focus in the digital age: Evidence from an e-commerce context | |
Areed et al. | Aspect-based sentiment analysis for Arabic government reviews | |
Shrestha et al. | Natural language processing based sentimental analysis of Hindi (SAH) script an optimization approach | |
Abro et al. | Natural language processing challenges and issues: A literature review | |
Diana et al. | Measuring performance of n-gram and Jaccard-similarity metrics in document plagiarism application | |
Haque et al. | Opinion mining from bangla and phonetic bangla reviews using vectorization methods | |
Zhang et al. | PKU paraphrase bank: A sentence-level paraphrase corpus for Chinese | |
Ojo et al. | Sentiment detection in economics texts | |
de Albornoz et al. | Using an Emotion-based Model and Sentiment Analysis Techniques to Classify Polarity for Reputation. | |
Yang et al. | News text mining-based business sentiment analysis and its significance in economy | |
WO2020091618A1 (en) | System for identifying named entities with dynamic parameters | |
Gupta et al. | A two-staged NLP-based framework for assessing the sentiments on Indian supreme court judgments | |
Malla et al. | An improved machine learning technique for identify informative COVID-19 tweets | |
Liu et al. | An empirical study on Chinese microblog stance detection using supervised and semi-supervised machine learning methods | |
Hott et al. | Evaluating contextualized embeddings for topic modeling in public bidding domain | |
Kang et al. | A short texts matching method using shallow features and deep features | |
Kour et al. | Lexicon-based sentiment analysis | |
Hristova | Topic modeling of chat data: A case study in the banking domain | |
Rajput et al. | Analysis of various sentiment analysis techniques | |
Palchunov et al. | Development of Logical Methods for Extracting Emotional Assessments from Natural Language Texts | |
Blekanov et al. | The ideal topic: Interdependence of topic interpretability and other quality features in topic modelling for short texts | |
Pankajakshan et al. | Detecting duplicate question pairs using glove embeddings and similarity measures | |
Sofi et al. | Aspect Based Sentiment Analysis: Feature Extraction using Latent Dirichlet Allocation (LDA) and Term Frequency-Inverse Document Frequency (TF-IDF) in Machine Learning (ML) |