IJMTES – A FUZZY NAIVE BAYES CLASSIFICATION USING CLASS SPECIFIC FEATURES FOR TEXT CATEGORIZATION

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : A FUZZY NAIVE BAYES CLASSIFICATION USING CLASS SPECIFIC FEATURES FOR TEXT CATEGORIZATION

Author’s Name : V Bharathi | P K Jayanivetha | K Kanniga | D Sharmilaraniunnamed

Volume 04 Issue 03 2017

ISSN no:  2348-3121

Page no: 103-107

Abstract – With the rapid growth of information text categorization has become one of the important technique for organizing and handling text data. It is most needed to label the documents automatically with pre-defined set of topics.  There are various techniques has been proposed for automatic text categorization.  A Bayesian classifier was used for automatic text categorization where the specific features subset for each class was selected. Then the selected features are given as input to the Bayesian classifier for text categorization. This approach has some drawbacks like computationally costlier, consuming more time and assumes independence of features. In order to overcome these issues and to improve the accuracy of text categorization Fuzzy naïve bayes classifier is proposed. In this text categorization is performed by using class specific features in fuzzy naïve bayes classifier. The experimental results are conducted to prove the effectiveness of the proposed method in terms of accuracy, F-measure and G-Mean.
Keywords – Text Categorization, Bayesian Classifier, Fuzzy Naïve Bayes Classifier, Fuzzy Rule

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