A Conscientious Rival Penalized Competitive Learning Text Clustering Algorithm.

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. [ABSTRACT FROM AUTHOR]