首页    期刊浏览 2024年11月26日 星期二
登录注册

文章基本信息

  • 标题:EFFICIENT CENTRIODS BASED CLUSTERING ALGORITHM WITH DATA INTELLIGENCE
  • 本地全文:下载
  • 作者:D.JOHN ARAVINDER ; DR.E.R.NAGANATHAN
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2013
  • 卷号:56
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:Cluster analysis is important technique to find the similar and dissimilar group in data mining. From two decade of data mining process, most of technique extracts irrelevant knowledge to domain. This is the main aim of this paper. This paper proposes a new centroid based clustering algorithm. And also this paper includes some additional intelligence or measures with clustering process. This measure supported to find the relationship between data objects and clusters apart from distances. This algorithm tests with some synthetic datasets. Experimental results shows domain related clusters and needs to test with real time datasets.
  • 关键词:Data Mining; Clustering; K-Means Algorithm; Actionable Clusters
国家哲学社会科学文献中心版权所有