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An Efficient Search Method of Product Reviews using Opinion Mining Techniques  

Yune, Hong-June (서울시립대학교 전자전기컴퓨터공학부)
Kim, Han-Joon (서울시립대학교 전자전기컴퓨터공학부)
Chang, Jae-Young (한성대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.16, no.2, 2010 , pp. 222-226 More about this Journal
Abstract
With the continuously increasing volume of e-commerce transactions, it is now popular to buy some products and to evaluate them on the World Wide Web. The product reviews are very useful to customers because they can make better decisions based on the indirect experiences obtainable through these reviews. However, since online shopping malls do not provide ranking results, it is not easy for users to read all the relevant review documents effectively. Product reviews include subjective and emotional opinions. Thus, the review search is different from the general web search in terms of ranking strategy. In this paper, we propose an effective method of ranking the reviews that can reflect user's intention by using opinion mining techniques. The proposed method analyzes product reviews with query words, and sentimental polarity of subjective opinions. Through diverse experiments, we show that our proposed method outperforms conventional ones.
Keywords
Opinion Mining; Opinion Search; Product Review; Sentimental Polarity; Entropy;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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