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OPINION ANALYSIS FOR ONLINE REVIEWS


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Sinopse

This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the problem of combination explosion encountered, a greedy algorithm is devised to select the base classifiers. Contents: Introduction Related Works Preliminaries Term's Sentiment-Based Review Opinion Analysis Multiple Classifier System for Opinion Analysis Optimization of Base Classifier Selection Opinion Spam Detection Conclusions Readership: Researchers, academics, professionals and graduate students in databases, artificial intelligence and pattern recognition.

Detalhes do Produto

    • Ano de Edição: 2016
    • Ano:  2016
    • País de Produção: Canada
    • Código de Barras:  2001041831309
    • ISBN:  9789813100466

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