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Survey of Text Mining I


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Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space model, statistical model, or even the graph theory. It will address document identification, clustering and categorizing documents, cleaning the text, and visualizing semantic models of text.

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  • ISBN-10: 0387955631
  • ISBN-13: 9780387955636
  • Publisher: Springer
  • Pages: 244
  • Date: September 2003

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artificial intelligence cluster data mining information retrieval machine learning mining statistics text mining science computational linguistics vector space model natural language processing knowledge retrieval consensus clustering

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jehubyvu

February 12, 2012, 12:21 am

Survey of Text Mining I: Clustering, Classification, and Retrieval (No. 1) (Hardcover) http://t.co/IvRQMGY4

jibamuget

February 7, 2012, 8:53 am

Survey of Text Mining I: Clustering, Classification, and Retrieval (No. 1) (Hardcover) http://t.co/c2wyPtbs