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Classifying product reviews from balanced datasets for Sentiment Analysis and Opinion Mining

Lu, Joan (2014) Classifying product reviews from balanced datasets for Sentiment Analysis and Opinion Mining. In: 6th International Conference on Multimedia, Computer Graphics and Broadcasting. MulGrab 2014 . IEEE, Hainan China, pp. 29-34. ISBN 978-1-4799-7763-5

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The Online reviews provided for a product enables web user to make decisions
appropriately. These reviews may be positive, negative or neutral in nature. Analyzing and
classifying such product reviews have attracted reasonable interest. It has become quite hard
to make decisions since we aren’t able to obtain the decisions quickly. Hence it is required to
classify the reviews from balanced data sets for analysis and opinion mining of any
applications. The reason for considering balanced data sets is that the decision will not be
biased on the category of reviews considered. We have carried out investigations using
similarity measures to categorize the reviews correctly. Experiments reveal that the reviews
that were mixed in nature were able to be grouped correctly.

Item Type: Book Chapter
AuthorSudhakaran, Periakaruppankaran_sudha@rediffmail.comUNSPECIFIED
AuthorHariharan, Shanmugasundarammailtos.hariharan@gmail.comUNSPECIFIED
Subjects: Q Science > Q Science (General)
Schools: School of Computing and Engineering
Related URLs:
Depositing User: Joan Lu
Date Deposited: 05 May 2015 15:50
Last Modified: 16 Nov 2015 00:39


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