Intelligent information filtering using rough sets

  • Ratanapakdee, Tithiwat (Research Center for Communications and Information Technology (ReCCIT), Department of Computer Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang) ;
  • Pinngern, Ouen (Research Center for Communications and Information Technology (ReCCIT), Department of Computer Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang)
  • Published : 2004.08.25

Abstract

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

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