A conscientious rival penalized competitive learning text clustering algorithm

Authors:
Mao-ting Gao;Zheng-ou Wang
Affiliations:
Institute of Systems Engineering, Tianjin University, Tianjin, China;Institute of Systems Engineering, Tianjin University, Tianjin, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

Text features are usually expressed as a huge dimensional vector in text mining, LSA can reduce dimensionality of text features effectively, and emerges the semantic relations between texts and terms. This paper presents a Conscientious Rival Penalized Competitive Learning (CRPCL) text clustering algorithm, which uses LSA to reduce the dimensionality and improves RPCL to set a conscientious threshold to restrict a winner that won too many times and to make every neural unit win the competition at near ideal probability. The experiments demonstrate good performance of this method.