Automatic extraction of features and Opinion-oriented sentences from customer reviews

Khan, K. and Baharudin, B.B. and Khan, A. and FazaleMalik (2010) Automatic extraction of features and Opinion-oriented sentences from customer reviews. World Academy of Science, Engineering and Technology, 62. pp. 457-461. ISSN 2010376X

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Abstract

Opinion extraction about products from customer reviews is becoming an interesting area of research. Customer reviews about products are nowadays available from blogs and review sites. Also tools are being developed for extraction of opinion from these reviews to help the user as well merchants to track the most suitable choice of product. Therefore efficient method and techniques are needed to extract opinions from review and blogs. As reviews of products mostly contains discussion about the features, functions and services, therefore, efficient techniques are required to extract user comments about the desired features, functions and services. In this paper we have proposed a novel idea to find features of product from user review in an efficient way. Our focus in this paper is to get the features and opinion-oriented words about products from text through auxiliary verbs (AV) is, was, are, were, has, have, had. From the results of our experiments we found that 82 of features and 85 of opinion-oriented sentences include AVs. Thus these AVs are good indicators of features and opinion orientation in customer reviews.

Item Type: Article
Additional Information: cited By 7
Uncontrolled Keywords: Automatic extraction; Classification; Customer review; Efficient method; Helping Verbs; Opinion extraction; Opinion mining; Method and technique, Customer satisfaction; Internet; Sales; Classification (of information), Feature extraction; Sales
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:49
Last Modified: 09 Nov 2023 15:49
URI: https://khub.utp.edu.my/scholars/id/eprint/1298

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