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http://dx.doi.org/10.9708/jksci.2010.15.11.021

A Study on the Characteristics of Opinion Retrieval Using Term Statistical Analysis in Opinion Documents  

Han, Kyoung-Soo (성결대학교 컴퓨터공학부)
Publication Information
Journal of the Korea Society of Computer and Information / v.15, no.11, 2010 , pp. 21-29 More about this Journal
Abstract
Opinion retrieval which searches the opinions expressed in documents by users cannot outperform significantly yet traditional topical retrieval which searches the facts. Therefore, the focus of this paper is to identify the statistical characteristics which can be applied to opinion retrieval by comparing and analyzing the term statistics of opinion and non-opinion documents in the blog domain. The TREC Blogs06 collection and 150 TREC topics are used in the experiments. The difference between term probability distributions in opinion documents is measured by JS divergence, and the difference according to the topic types and topic domains is also investigated. Moreover, the term probabilities of opinion terms are analyzed comparatively. The main findings of this study include the following: it is necessary to consider the topic-specific characteristics for the opinion detection; it is effective to extract positive and negative opinion terms according to the topics; the topic types are complementary to the topic domains; and special attention has to be given to the usage of the positive opinion terms.
Keywords
Opinion Retrieval; Opinion Detection; Opinion Terms;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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