文章基本信息

标题：Efficient Incremental Clustering of Documents based on Correlation
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作者：A.Devender ; B.Srinivas ; A.Ashok 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2015
卷号：4
期号：8
页码：13704-13709
DOI：10.18535/ijecs/v4i8.15
出版社：IJECS
摘要：With this project, a few dynamic file clustering algorithms, namely: Term consistency based GreatestResemblance Doc Clustering (TMARDC), Correlated Concept primarily based MAximum Resemblance DocumentClustering (CCMARDC) and Correlated Notion based Quickly Incremental Clustering Criteria (CCFICA) usually areproposed. From the aforementioned three suggested algorithms this TMARDC algorithm will be based upon termconsistency, whereas, the CCMARDC and CCFICA are based on Correlated conditions (Terms and their Associatedterms) notion extraction protocol
关键词：Clustering; Document Analysis