A Novel Text Clustering Algorithm.

Abstract: The partitional clustering algorithms are used more widely in text clustering. However, the traditional algorithms based on partition treat all the attributes equally in clustering process. They all suppose that the importance of each attribute is equal. These algorithms will have a lower accuracy. In order to handle this problem, this paper provides a new clustering algorithm-attribute weighted fuzzy c-means algorithm. During the iteration of this algorithm, it can find the important attributes. Moreover, this algorithm also can find the cluster structure hiding by the unimportant attributes. The simulation of this algorithm on test documents can prove the algorithm provided by this paper can gain a good computation speed, found the latent structure and can remark the different importance of each attribute. [Copyright &y& Elsevier]