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  • 标题:Survey on Feature Selection in Document Clustering
  • 本地全文:下载
  • 作者:MS. K.Mugunthadevi ; MRS. S.C. Punitha ; Dr..M. Punithavalli
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:03
  • 页码:1240-1244
  • 出版社:Engg Journals Publications
  • 摘要:Text mining is to research technologies to discover useful knowledge from enormous collections of documents, and to develop a system to provide knowledge and to support in decision making. Basically cluster means a group of similar data, document clustering means segregating the data into different groups of similar data. Clustering is a fundamental data analysis technique used for various applications such as biology, psychology, control and signal processing, information theory and mining technologies. Text mining is not a stand-alone task that human analysts typically engage in. The goal is to transform text composed of everyday language into a structured, database format. In this way, heterogeneous documents are summarized and presented in a uniform manner. Among others, the challenging problems of text clustering are big volume, high dimensionality and complex semantics.
  • 关键词:text mining; feature selection; information retrieval; ontology; document clustering
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