期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：5
出版社：S.S. Mishra
摘要：The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure. In data mining K-means clustering algorithm is one of the efficient unsupervised learning algorithms to solve the well-known clustering problems. The disadvantage in k-means algorithm is that, the accuracy and efficiency is varied with the choice of initial clustering centers on choosing it randomly. So in this paper, less similarity based clustering method is proposed for finding the better initial centroids and to provide an efficient way of assigning the data points to suitable clusters with reduced time complexity. They mainly classified into three main categories: text-based, link-based and hybrid.
