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EBOOK
Author Bhatia, Surbhi.
Title Opinion mining in information retrieval / Surbhi Bhatia, Poonam Chaudhary, Nilanjan Dey.
Imprint Singapore : Springer, 2020.

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 OHIOLINK SPRINGER EBOOKS    ONLINE  
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Author Bhatia, Surbhi.
Series SpringerBriefs in Applied Sciences and Technology, Computational intelligence.
SpringerBriefs in applied sciences and technology. Computational intelligence.
Subject Data mining.
Information retrieval.
Alt Name Chaudhary, Poonam.
Dey, Nilanjan, 1984-
LOCATION CALL # STATUS MESSAGE
 OHIOLINK SPRINGER EBOOKS    ONLINE  
View online
Author Bhatia, Surbhi.
Series SpringerBriefs in Applied Sciences and Technology, Computational intelligence.
SpringerBriefs in applied sciences and technology. Computational intelligence.
Subject Data mining.
Information retrieval.
Alt Name Chaudhary, Poonam.
Dey, Nilanjan, 1984-
Description 1 online resource (119 pages).
Note Description based upon print version of record.
7.2 Datasets and Evaluations
Contents Intro -- Preface -- About This Book -- Contents -- About the Authors -- 1 Introduction to Opinion Mining -- 1.1 Opinions: A Cognitive Source of Information -- 1.1.1 Necessity for E-commerce: A New Trend in Online Shopping -- 1.1.2 Facts and Opinions: Types of Opinion -- 1.1.3 Demand for Information on Opinions -- 1.1.4 Google: Not as Effective for Searching Opinions -- 1.2 Understanding Opinion Mining -- 1.2.1 Definition of Opinion Mining by Various Researchers -- 1.2.2 Levels of Opinion Mining -- 1.2.3 Components of Opinion Mining -- 1.2.4 Applications in Opinion Mining
1.3 Steps in Opinion Mining -- 1.3.1 Opinion Retrieval -- 1.3.2 Opinion Detection -- 1.3.3 Aspect Detection -- 1.3.4 Opinion Classification -- 1.3.5 Opinion Summarization -- 1.4 Information Retrieval: Challenges in Mining Opinions -- 1.4.1 Introduction to IR -- 1.4.2 Present Opinion Mining Systems -- 1.4.3 Challenges: Factors that Make Opinion Mining Difficult -- 1.4.4 Our Charge and Approach -- 1.5 Summary -- References -- 2 Opinion Score Mining System -- 2.1 Framework Design -- 2.1.1 Opinion Retrieval -- 2.1.2 Opinion Identification -- 2.1.3 Opinion Classification -- 2.1.4 Opinion Summarization
2.2 Opinion Score Mining System (OSMS) -- 2.2.1 Opinion Crawling and Pre-processing Opinions -- 2.2.2 Aspect Identification and Classification of Opinions -- 2.2.3 Aspect Based Opinion Summarization -- 2.2.4 Look up for Alternate Data -- 2.3 Summary -- References -- 3 Opinion Retrieval -- 3.1 Introduction -- 3.2 Extraction of Opinions from Text -- 3.2.1 Web Search Versus Opinion Search -- 3.2.2 Challenges in Retrieving Opinion -- 3.2.3 Existing Opinion Retrieval Techniques -- 3.3 Opinion Spam Detection -- 3.3.1 Spam Types -- 3.3.2 Fake Reviews -- 3.3.3 Spam Detection Methods
3.4 Cleaning Opinions -- 3.4.1 Preprocessing and Its Tasks -- 3.5 Crawling Opinions -- 3.6 Summary -- References -- 4 Aspect Extraction -- 4.1 Product Features Mining -- 4.2 Opinion Word Extraction -- 4.3 Features Opinion Pair Generation -- 4.4 Summary -- References -- 5 Opinion Classification -- 5.1 Sentiment Analysis and Opinion Classification -- 5.1.1 Problem in AI Context -- 5.1.2 Document-Level Classification -- 5.1.3 Sentence Subjectivity -- 5.2 Opinion Strength and Polarity Generation -- 5.2.1 Dictionary-Based Approaches -- 5.2.2 Machine Learning Techniques
5.2.3 Traditional Supervised Learning Models -- 5.2.4 What's Ahead -- 5.3 Deep Learning in Opinion Mining -- 5.4 Aspect-Based Opinion Classification -- 5.5 Summary -- References -- 6 Opinion Summarization -- 6.1 Text Summarization -- 6.1.1 Extractive Summarization -- 6.1.2 Abstractive Summarization -- 6.2 Traditional Approaches -- 6.2.1 Supervised Learning Techniques -- 6.2.2 Unsupervised Learning Techniques -- 6.3 Summary Generation -- 6.3.1 Opinion Aggregation -- 6.4 Aspect-Based Opinion Summarization -- 6.5 Summary -- References -- 7 Conclusions -- 7.1 Tools and Techniques
Summary 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 todays society. In the past, peoples 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 ones 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 shown that many organizations have improved their sales, marketing and strategy, setting up new policies and making decisions based on opinion mining techniques.
ISBN 9789811550430 (electronic bk.)
9811550433 (electronic bk.)
9789811550423 (print)
9811550425
ISBN/ISSN 10.1007/978-981-15-5
OCLC # 1155332518
Additional Format Print version: Bhatia, Surbhi Opinion Mining in Information Retrieval Singapore : Springer,c2020 9789811550423.


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