Text clustering method based on centers of initial cluster and anew rescaling function
初始化簇类中心和重构标度函数的文本聚类*

According to the text set center and initial cluster center,in the text clustering process, this paper chose a set of discriminative directions to construct the IMIC coordinate, and constructed each axis to re-scaling function in order to improve the effectiveness of cluster policy,according to the distribution characteristics of the initial clusters. IMIC iterative algorithm ways converged to the final solution.The time complexity of IMIC remained the same as K-means by using a K-means-like ite-ration strategy. Experimental results show that IMIC algorithm has better clustering quality.