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Record Nr. |
UNINA9910483489703321 |
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Autore |
Bhatia Surbhi |
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Titolo |
Opinion Mining in Information Retrieval / / by Surbhi Bhatia, Poonam Chaudhary, Nilanjan Dey |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (119 pages) |
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Collana |
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SpringerBriefs in Computational Intelligence, , 2625-3704 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Machine learning |
Artificial intelligence |
Data mining |
Computational Intelligence |
Machine Learning |
Artificial Intelligence |
Data Mining and Knowledge Discovery |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Chapter 1. Introduction to Opinion Mining -- Chapter 2. Opinion Score Mining System -- Chapter 3. Opinion Retrieval -- Chapter 4. Aspect Extraction -- Chapter 5. Opinion Classification -- Chapter 6. Opinion Summarization -- Chapter 7. Conclusions. |
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Sommario/riassunto |
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This book discusses in detail the latest trends in sentiment analysis,focusing on “how online reviews and feedback reflect the opinions of users and have led to a major shift in the decision-making process at organizations.” Social networking has become essential in today’s society. In the past, people’s decisions to buy certain products (and companies’ efforts to sell them) were largely based on advertisements, surveys, focus groups, consultants, and the opinions of friends and relatives. But now this is no longer limited to one’s circle of friends, family or small surveys;it has spread globally to online social media in the form of blogs, posts, tweets, social networking sites, review sites and so on. Though not always easy, the transition from surveys to social media is certainly lucrative. Business analytical reports have |
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shown that many organizations have improved their sales, marketing and strategy, setting up new policies and making decisions based on opinion mining techniques. . |
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