Feature Selection and Document Clustering

نویسندگان

  • Inderjit Dhillon
  • Jacob Kogan
  • Charles Nicholas
چکیده

Feature selection is a basic step in the construction of a vector space or bag of words model [BB99]. In particular, when the processing task is to partition a given document collection into clusters of similar documents a choice of good features along with good clustering algorithms is of paramount importance. This chapter suggests two techniques for feature or term selection along with a number of clustering strategies. The selection techniques significantly reduce the dimension of the vector space model. Examples that illustrate the effectiveness of the proposed algorithms are provided.

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تاریخ انتشار 2002