A method for opinion mining of product reviews using association rules

Published 24 November 2009

Won Young Kim, Joon Suk Ryu, Kyu Il Kim, Ung Mo Kim

Citations31

TL;DR

In this paper, a proposed opinion mining method for product reviews is proposed by doing POS tagging on each review sentence, and extracting feature and opinion words in form of transaction data from the transaction data using PMI-IR algorithm.

Abstract

When most people buy the products, they inquire about other people's opinion and refer to recommended product. Today, the result of explosive development of the Web makes it easy to consult other people's opinion information. These variety of opinion data are not only useful to customers, but also manufacturers. As a result, opinion mining research to analyze opinion data on the web has become a popular topic recently. In this paper, we proposed opinion mining method for product reviews. In our approach, we first do POS tagging on each review sentence, and we extract feature and opinion words in form of transaction data. Then we discover association rules of needed type from the transaction data, and provide information that is summarized advantages and disadvantages using PMI-IR algorithm.

Keywords

Computer Science

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