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Extracting knowledge from opinion mining[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.3/12
書名/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.
標題:	Discourse analysis - Data processing.
標題:	Language and emotions.
標題:	Public opinion.
ISBN:	9781522561187 (e-book)
ISBN:	9781522561170 (hardback)
書目註:	Includes bibliographical references and index.
內容註:	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
摘要、提要註:	"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.
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-6117-0

Extracting knowledge from opinion mining[electronic resource] /
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:

337740
Data mining.

LC Class. No.: QA76.9.D343 / E9984 2019e

Dewey Class. No.: 006.3/12

Extracting knowledge from opinion mining[electronic resource] /
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245 0 0 $a Extracting knowledge from opinion mining $h [electronic resource] / $c Rashmi Agrawal and Neha Gupta, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c [2019]
300 $a 1 online resource (xxvii, 346 p.)
504 $a Includes bibliographical references and index.
505 0 $a 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
506 $a Restricted to subscribers or individual electronic text purchasers.
520 3 $a "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.
650 0 $a Data mining. $3 337740
650 0 $a Discourse analysis $x Data processing. $3 387091
650 0 $a Language and emotions. $3 349735
650 0 $a Public opinion. $3 204636
700 1 $a Agrawal, Rashmi, $e editor. $3 734566
700 1 $a Gupta, Neha, $e editor. $3 734567
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-6117-0