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Extracting knowledge from opinion mining
~
Gupta, Neha,
Extracting knowledge from opinion mining
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Extracting knowledge from opinion mining/ Rashmi Agrawal and Neha Gupta, editors.
其他作者:
Agrawal, Rashmi,
出版者:
Hershey, Pennsylvania :IGI Global, : [2019],
面頁冊數:
1 online resource (xxvii, 346 p.)
標題:
Data mining. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-6117-0
ISBN:
9781522561187 (e-book)
Extracting knowledge from opinion mining
Extracting knowledge from opinion mining
[electronic resource] /Rashmi Agrawal and Neha Gupta, editors. - Hershey, Pennsylvania :IGI Global,[2019] - 1 online resource (xxvii, 346 p.)
Includes bibliographical references and index.
Section 1. Introductory concepts of opinion mining. Chapter 1. Fundamentals of opinion mining ; Chapter 2. Feature based opinion mining ; Chapter 3. Deep learning for opinion mining ; Chapter 4. Opinion mining: using machine learning techniques -- Section 2. Ontologies and their applications. Chapter 5. Ontology-based opinion mining ; Chapter 6. Ontologies, repository, and information mining in component-based software engineering environment ; Chapter 7. Ontology-based opinion mining for online product reviews ; Chapter 8. Applications of ontology-based opinion mining -- Section 3. Tools and techniques of opinion mining. Chapter 9. Tools of opinion mining ; Chapter 10. Sentimental analysis tools ; Chapter 11. Anatomizing lexicon with natural language Tokenizer Toolkit 3 -- Section 4. Challenges and open issues of opinion mining. Chapter 12. Challenges of text analytics in opinion mining ; Chapter 13. Open issues in opinion mining -- Section 5. Case study. Chapter 14. Case study: efficient faculty recruitment using genetic algorithm
Restricted to subscribers or individual electronic text purchasers.
"This book covers the key topics of opinion mining and sentiment analysis. It includes future trends and research directions related to opinion supervised and unsupervised approaches for opinion mining, machine learning techniques, deep learning and opinion spam detection. The book also includes some open source tools for opinion mining and sentiment analysis"--Provided by publisher.
ISBN: 9781522561187 (e-book)Subjects--Topical Terms:
528622
Data mining.
LC Class. No.: QA76.9.D343 / E9984 2019e
Dewey Class. No.: 006.3/12
Extracting knowledge from opinion mining
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Section 1. Introductory concepts of opinion mining. Chapter 1. Fundamentals of opinion mining ; Chapter 2. Feature based opinion mining ; Chapter 3. Deep learning for opinion mining ; Chapter 4. Opinion mining: using machine learning techniques -- Section 2. Ontologies and their applications. Chapter 5. Ontology-based opinion mining ; Chapter 6. Ontologies, repository, and information mining in component-based software engineering environment ; Chapter 7. Ontology-based opinion mining for online product reviews ; Chapter 8. Applications of ontology-based opinion mining -- Section 3. Tools and techniques of opinion mining. Chapter 9. Tools of opinion mining ; Chapter 10. Sentimental analysis tools ; Chapter 11. Anatomizing lexicon with natural language Tokenizer Toolkit 3 -- Section 4. Challenges and open issues of opinion mining. Chapter 12. Challenges of text analytics in opinion mining ; Chapter 13. Open issues in opinion mining -- Section 5. Case study. Chapter 14. Case study: efficient faculty recruitment using genetic algorithm
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"This book covers the key topics of opinion mining and sentiment analysis. It includes future trends and research directions related to opinion supervised and unsupervised approaches for opinion mining, machine learning techniques, deep learning and opinion spam detection. The book also includes some open source tools for opinion mining and sentiment analysis"--Provided by publisher.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-6117-0
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