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An enhanced text classifier for automatic document classification

Authors:

PKCM Wijewickrema ,

Sabaragamuwa University of Sri Lanka, LK
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RCG Gamage

University of Moratuwa,, LK
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Abstract

Automatic classification has become an important research area due to the exponential growth of digital content in the modern world. Evidently, manual classification of documents is very painstaking and laborintensive task. It takes much time to organize a collection of documents according to the subject area. This research has developed a computer programme that can automatically classifying a given text document. Therefore, the user gets correct classification results just after feeding the document to the new system. For the process of classification, we use a new algorithm developed by enhancing basic form of an existing text classifier called tf-idf. The results were obtained for classification accuracy of the new text classification algorithm. They were compared with the results obtained for the basic tf-idf classifier. The research revealed that, the newly developed classifier algorithm can obtain better classification accuracy than the basic tf-idf classifier.

Journal of the University Librarians Association, Sri Lanka, Vol. 16, Issue 2, July 2012, Page 138-159

DOI: http://dx.doi.org/10.4038/jula.v16i2.5205

How to Cite: Wijewickrema, P. & Gamage, R., (2013). An enhanced text classifier for automatic document classification. Journal of the University Librarians Association of Sri Lanka. 16(2), pp.138–159. DOI: http://doi.org/10.4038/jula.v16i2.5205
Published on 04 Feb 2013.
Peer Reviewed

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