Text Mining Algorithm Based on Fuzzy Clustering
Zhiyong Liu, Xinqing Geng · Jisuanji gongcheng · 2009
The main defect of traditional methods of FCM algorithm is sensitive to the isolated data and is to know the number of clustering in advance.A fuzzy clustering algorithm NSFCM is presented in this paper,and NSFCM agorithm is applied to text mining.This algorithm adds a weight to the membership of the data,which is to decrease the effect on the initial cluster center.This paper applies average information entropy to find the number of clusters and adopts a density function algorithm to find the initial cluster centers.The experiment shows both the precision and the efficiency of clustering NSFCM are higher than those of FCM.