A novel algorithm for text categorization using improved back-propagation neural network

Authors:
Cheng Hua Li;Soon Cheol Park
Affiliations:
Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea;Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea
Venue:
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Year:
2006

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Abstract

This paper describes a novel adaptive learning approach for text categorization based on a Back-propagation neural network (BPNN). The BPNN has been widely used in classification and pattern recognition; however it has some generally acknowledged defects, which usually originate from some morbidity neurons. In this paper, we introduce an improved BPNN that can overcome these defects and rectify the morbidity neurons. We tested the improved model on the standard Reuter-21578, and the result shows that the proposed model is able to achieve high categorization effectiveness as measured by the precision, recall and F-measure.