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  • 标题:Clustering Techniques on Text Mining: A Review
  • 本地全文:下载
  • 作者:Neha Garg ; R. K. Gupta
  • 期刊名称:International Journal of Engineering Research
  • 印刷版ISSN:2319-6890
  • 出版年度:2016
  • 卷号:5
  • 期号:4
  • 页码:241-243
  • DOI:10.17950/ijer/v5s4/404
  • 出版社:IJER
  • 摘要:Rapid advancements of smart technologies, permits the individuals and organizations to store large number of documents in repositories. But it is quite difficult to retrieve the relevant documents from these massive collections. Document clustering is the process of organizing such massive document collections into meaningful clusters. It is simple and less tedious to find relevant documents, if documents are clustered on the basis of topic or category. There are various document clustering algorithms available for effectively organizing the documents such that a document is close to its related documents. This paper presents various clustering techniques that are being used in text mining.
  • 关键词:Text mining; Preprocessing; Vector Space ; Model; Clustering algorithms
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