文章基本信息

标题：A SURVEY ON ENHANCED APPROACH FOR CATEGORICAL LINK BASED CLUSTERING
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作者：C.M.Geetha ; K.Sangeetha ; S.Karthik 等
期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2013
卷号：2
期号：1
页码：142-144
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Data clustering is a challenging task in data mining technique. Various clustering algorithms are developed to cluster or categorize the datasets. Many algorithms are used to cluster the categorical data. Some algorithms cannot be directly applied for clustering of categorical data. Several attempts have been made to solve the problem of clustering categorical data via cluster ensembles. But these techniques generate a final data partition based on incomplete information. The ensemble information matrix represents cluster relations with many unknown entries. The link based ensemble approach has been established with the ability to discover unknown values and improve the accuracy of the data partition. Besides clustering, similarity based ranking approach, HITS link analysis is also proposed to enhance the categorical results. This enhanced link-based clustering and ranking method almost outperforms both conventional clustering algorithms for categorical data and well-known cluster ensemble techniques for ranking.
关键词：Clustering; categorical data; cluster ; ensemble;ranking