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A sentiment-based meta search engine

Na, Jin-Cheon and Khoo, Christopher S.G. and Chan, Syin (2006) A sentiment-based meta search engine. In Khoo, C. and Singh, D. and Chaudhry, A.S., Eds. Proceedings A-LIEP 2006: Asia-Pacific Conference on Library & Information Education & Practice 2006 (A-LIEP 2006), pages pp. 83-89, Singapore.

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Abstract

This study is in the area of sentiment classification—classifying online review documents according to the overall sentiment expressed in them. This paper presents a prototype sentiment-based meta search engine that has been developed to perform sentiment categorization of Web search results. It assists users to quickly focus on recommended or non-recommended information by classifying Web search results into four categories: positive, negative, neutral, and non-review documents. It does this by using an automatic classifier based on a supervised machine learning algorithm, Support Vector Machine (SVM). This paper also discusses various issues we have encountered during the prototype development, and presents our approaches for resolving them. A user evaluation of the prototype was carried out with positive responses from users.

EPrint Type:Conference Paper
Keywords:Sentiment classification, Meta search engine
Subjects:Classification
Web Mining
Information Retrieval
Natural Language Processing
ID Code:1365
Deposited On:22 May 2007
Eprint Statistics:View statistics for this eprint
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