Classifying Product Reviews from Balanced Datasets for Sentiment Analysis and Opinion Mining

Periakaruppan Sudhakaran, Shanmugasundaram Hariharan, Joan Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 6th International Conference on Multimedia, Computer Graphics and Broadcasting, MulGraB 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-34
Number of pages6
ISBN (Electronic)9781479977642
DOIs
Publication statusPublished - 27 Jan 2015
Event6th International Conference on Multimedia, Computer Graphics and Broadcasting - Hainan, China
Duration: 20 Dec 201423 Dec 2014
Conference number: 6
http://www.conferen.org/MulGraB2014/ (Link to Conference Website )

Conference

Conference6th International Conference on Multimedia, Computer Graphics and Broadcasting
Abbreviated titleMulGraB 2014
CountryChina
CityHainan
Period20/12/1423/12/14
Internet address

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