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文章基本信息

  • 标题:A Theoretical Study of Text Document Clustering
  • 本地全文:下载
  • 作者:Yogesh Jain ; Amit Kumar Nandanwar
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2014
  • 卷号:5
  • 期号:2
  • 页码:2246-2251
  • 出版社:TechScience Publications
  • 摘要:The objective of clustering is to partition an unstructured set of objects into clusters (groups). One often wants to group similar objects in same cluster and dissimilar in different clusters as far as feasibly possible. Clustering is a widely studied data mining problem in text domain. The aim of this paper is to provide an understanding about applying clustering to text documents. It thoroughly discusses about document pre-processing, applications of text clustering, key methods for text clustering, their relative advantages and limitations. Besides this, we will also discuss recent advances in this area.
  • 关键词:Text clustering; Feature selection; Preprocessing.
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