期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：8
页码：3333-3336
出版社：Shri Pannalal Research Institute of Technolgy
摘要：This paper presents comparative results of an experimental study of traditional clustering algorithm and proposed clustering algorithm. In particular, we compare the two approaches to text data clustering, WDC-CSK clustering algorithm and our proposed algorithm (i.e. based on K-mean algorithm and fuzzy logic.) traditional clustering algorithm is automatically defining number of clusters and deliver appropriate results for high dimensional data , but is limited because of it uses n number of iteration and population size. Number of iteration and population is not sufficient. So in order to reduce number of iteration and to use and enhance the traditional technique a novel approach is required to design by which accuracy, memory consumption, time complexity, error rate, precision and recall are improved.
关键词：text mining; clustering; information extraction; ; information retrieval; k-mean; metadata; natural language ; processing etc
