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Sentiment Analysis

Mining Opinions, Sentiments, And Emotions

Sentiment Analysis - Liu, Bing (university Of Illinois, Chicago) - ISBN: 9781107017894
Prijs: € 74,90 (onder voorbehoud)
Beschikbaarheid: Uitverkocht (U kunt dit boek niet meer bestellen)
Bindwijze: Boek, Gebonden
Genre: Databases
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Beschrijving

This book gives a comprehensive introduction to all the core areas and many emerging themes of sentiment analysis.

Details

Titel: Sentiment Analysis
auteur: Liu, Bing (university Of Illinois, Chicago)
Mediatype: Boek
Bindwijze: Gebonden
Taal: Engels
Aantal pagina's: 381
Uitgever: Cambridge University Press
Plaats van publicatie: 01
NUR: Databases
Afmetingen: 165 x 241 x 28
Gewicht: 734 gr
ISBN/ISBN13: 9781107017894
Intern nummer: 27474967

Biografie (woord)

Bing Liu is a Professor of Computer Science at the University of Illinois. His current research interests include sentiment analysis and opinion mining, data mining, machine learning, and natural language processing. He has published extensively in top conferences and journals, and his research has been cited on the front page of the New York Times. He is also the author of two books: Sentiment Analysis and Opinion Mining (2012) and Web Data Mining: Exploring Hyperlinks, Contents and Usage Data (1st edition, 2007; 2nd edition, 2011). He currently serves as the chair of ACM SIGKDD and is an IEEE Fellow.

Quote

'As a whole, this book serves as a useful introduction to sentiment analysis along with in-depth discussions of linguistic phenomena related to sentiments, opinions, and emotions. Although many sentiment analysis methods are based on machine learning as in other NLP [Natural Language Processing] tasks, sentiment analysis is much more than just a classification or regression problem, because the natural language constructs used to express opinions, sentiments, and emotions are highly sophisticated, including sentiment shift, implicated expression, sarcasm, and so on. Liu has described these issues and problems very clearly. Readers will find this book to be inspiring and it will arouse their interests in sentiment analysis.' Jun Zhao, Computational Linguistics

Inhoudsopgave

1. Introduction; 2. The problem of sentiment analysis; 3. Document sentiment classification; 4. Sentence subjectivity and sentiment classification; 5. Aspect sentiment classification; 6. Aspect and entity extraction; 7. Sentiment lexicon generation; 8. Analysis of comparative opinions; 9. Opinion summarization and search; 10. Analysis of debates and comments; 11. Mining intentions; 12. Detecting fake or deceptive opinions; 13. Quality of reviews.

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