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http://dx.doi.org/10.3837/tiis.2015.05.008

A Personalized Approach for Recommending Useful Product Reviews Based on Information Gain  

Choeh, Joon Yeon (Department of Digital Contents, Sejong University)
Lee, Hong Joo (Department of Business Administration, The Catholic University of Korea)
Park, Sung Joo (KAIST Business School)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.9, no.5, 2015 , pp. 1702-1716 More about this Journal
Abstract
Customer product reviews have become great influencers of purchase decision making. To assist potential customers, online stores provide various ways to sort customer reviews. Different methods have been developed to identify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most of the methods consider the preferences of all users to determine whether reviews are helpful, and all users receive the same recommendations.
Keywords
Product review; Personalization; Text mining; Information gain;
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