Wang et al., 2018 - Google Patents
A novel feature-based text classification improving the accuracy of twitter sentiment analysisWang et al., 2018
- Document ID
- 3185434248426413851
- Author
- Wang Y
- Sun L
- Wang J
- Zheng Y
- Youn H
- Publication year
- Publication venue
- Advances in Computer Science and Ubiquitous Computing: CSA-CUTE 17
External Links
Snippet
With the growth of Internet and various online services, tremendous amount of data are generated in real time. As a result, sentiment analysis of online reviews has become an important research problem. In this paper a novel feature selection and weighting scheme is …
- 230000002996 emotional 0 abstract description 11
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
- G06F17/30705—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
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
-
- 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
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- 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
- 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
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- 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
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- 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
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Talpur et al. | Cyberbullying severity detection: A machine learning approach | |
Daud et al. | Using machine learning techniques for rising star prediction in co-author network | |
Wang et al. | Word clustering based on POS feature for efficient twitter sentiment analysis | |
US11573995B2 (en) | Analyzing the tone of textual data | |
WO2019043379A1 (en) | Fact checking | |
Chen et al. | A comparison of classical versus deep learning techniques for abusive content detection on social media sites | |
Burdisso et al. | τ-SS3: A text classifier with dynamic n-grams for early risk detection over text streams | |
Lee et al. | Sentiment labeling for extending initial labeled data to improve semi-supervised sentiment classification | |
Ashok et al. | A personalized recommender system using machine learning based sentiment analysis over social data | |
Karamollaoğlu et al. | Sentiment analysis on Turkish social media shares through lexicon based approach | |
Mounika et al. | Design of book recommendation system using sentiment analysis | |
Geetha et al. | Tweet analysis based on distinct opinion of social media users’ | |
Kaur et al. | A comprehensive overview of sentiment analysis and fake review detection | |
Jiang et al. | Sentiment analysis for troll detection on Weibo | |
Joshi et al. | An Inventive Movie Suggestion System Using Machine Learning Techniques | |
Aquino et al. | Opinion mining system for twitter sentiment analysis | |
Jiang et al. | Detecting online fake reviews via hierarchical neural networks and multivariate features | |
Guo et al. | Who is answering to whom? Finding “reply-to” relations in group chats with long short-term memory networks | |
Jeong et al. | Discovery of research interests of authors over time using a topic model | |
Wang et al. | A novel feature-based text classification improving the accuracy of twitter sentiment analysis | |
Akkarapatty et al. | Dimensionality reduction techniques for text mining | |
Sisodia et al. | Performance evaluation of learners for analyzing the hotel customer sentiments based on text reviews | |
Hu et al. | Memory-enhanced latent semantic model: short text understanding for sentiment analysis | |
Kumar et al. | Social media analysis for sentiment classification using gradient boosting machines | |
Kim et al. | The power of communities: A text classification model with automated labeling process using network community detection |