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Book Synopsis
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.

Opinion Analysis For Online Reviews

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Order before 4pm tomorrow for delivery by Tue 20 Jan 2026.

A Hardback by Yuming Lin, Xiaoling Wang, Aoying Zhou

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    View other formats and editions of Opinion Analysis For Online Reviews by Yuming Lin

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 28/07/2016
    ISBN13: 9789813100435, 978-9813100435
    ISBN10: 9813100435
    Also in:
    Data capture and analysis

    Description

    Book Synopsis
    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.

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