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  An SVM Classifier using Correlation based Feature   Selection for Opinion Mining
     
    International Conference on Infomration System, Computer Engineering & Application ( ICISCEA 2011 )
    © 2011 by OLS Journal - ISSN No : 2091- 0266
    Number 1
    Year of Publication : December Issue , 2011
    Authors : J.Isabella , R.M.Suresh 
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  Citation J.Isabella , R.M.Suresh : An SVM Classifier using Correlation based Feature   Selection for Opinion Mining: OLS Journals Special Isssue onInfomration System, Computer Engineering & Application , 2011 , Published by : OLS Journals
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  Abstract  
 

 Online reviews are popular way to judge the quality  of product. The customer’s feedback on websites, blog, influences  other customer’s decision. Thus it has become increasingly  important for the businesses to keep track of the feedback to  develop marketing, upgrade product and services. Feedbacks are  available at different forums such as review websites, discussion forums, and blogs. Opinion mining is an efficient way to automatically extract and process reviews and provide a summary of required information. In this paper it is proposed to  extract the feature set from movie opinions. Inverse document  frequency is computed and the feature set is reduced using the  proposed correlation based feature reduction. The proposed preprocessing method efficacy is tested using Naive Bayes and  Support Vector Machine classifier.

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  Keywords

:Opinion mining, IMDb, Inverse document frequency  (IDF), Naïve Bayes, Support Vector Machine.
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