Building Text Knowledge Map for Product Development Based on CSEP Method

In the text clustering, K-means clustering algorithm often stops at the place of local optimization and finding the global optimization using it is very difficult. This paper proposes a new text clustering method based on the CSEP (chaotic social evolutionary programming) algorithm. In this method, we present the manner of that a cognitive agent inherits a paradigm in clustering, and a chaotic mutation operator is used for the betrayal of a cognitive agent to a paradigm. The experiments demonstrate that the present method not only can effectively improve the efficiency of text clustering but also can effectively improve precision of text clustering. Based on this, we build text knowledge map for product development using CSEP method.