文章基本信息

标题：Exploration of Various Clustering Algorithms for Text Mining
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作者：Neha Garg ; R.K. Gupta
期刊名称：International Journal of Education and Management Engineering(IJEME)
印刷版ISSN：2305-3623
电子版ISSN：2305-8463
出版年度：2018
卷号：8
期号：4
页码：10-18
DOI：10.5815/ijeme.2018.04.02
出版社：MECS Publisher
摘要：Due to the current encroachments in technology and also sharp lessening of storage cost, huge extents of documents are being put away in repositories for future references. At the same time, it is time consuming as well as costly to recover the user intrigued documents, out of these gigantic accumulations. Searching of documents can be made more efficient and effective if documents are clustered on the premise of their contents. This article uncovers a comprehensive discussion on various clustering algorithm used in text mining alongside their merits, demerits and comparisons. Further, author has likewise examined the key challenges of clustering algorithms being used for effective clustering of documents.
关键词：Text Mining;Document Clustering;Partitioning Algorithms;Hierarchical Algorithms