A symbolic approach for text classification based on dissimilarity measure

Authors:
B. S. Harish;D. S. Guru;S. Manjunath;Bapu B. Kiranagi
Affiliations:
University of Mysore, Manasagangotri, Mysore, India;University of Mysore, Manasagangotri, Mysore, India;University of Mysore, Manasagangotri, Mysore, India;University of Mysore, Manasagangotri, Mysore, India
Venue:
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Year:
2010

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Abstract

In this paper, a simple and efficient symbolic text classification is presented. A text document is represented by the use of interval valued symbolic features. Subsequently, a new feature selection method based on a new dissimilarity measure is also presented. The new feature selection method reduces the features in the representation phase for effective text classification. It keeps the best features for effective text representation and simultaneously reduces the time taken to classify a given document. To corroborate the efficacy of the proposed method, experimentation has been conducted on four different datasets to evaluate the performance. Experimental results reveal that the proposed method gives better results when compare to state of the art techniques. In addition, as it is based on simple matching scheme it achieves classification within negligible time and thus it appear to be more effective in classification.