• DocumentCode
    658645
  • Title

    Tolerance Rough Set Model and Its Applications in Web Intelligence

  • Author

    Hung Son Nguyen

  • Author_Institution
    Inst. of Math., Univ. of Warsaw, Warsaw, Poland
  • Volume
    3
  • fYear
    2013
  • fDate
    17-20 Nov. 2013
  • Firstpage
    237
  • Lastpage
    244
  • Abstract
    Tolerance Rough Set Model (TRSM) has been introduced as a tool for approximation of hidden concepts in text databases. In recent years, numerous successful applications of TRSM in web intelligence including text classification, clustering, thesaurus generation, semantic indexing, and semantic search, etc., have been proposed. This paper will review the fundamental concepts of TRSM, some of its possible extensions and some typical applications of TRSM in text mining. Moreover, the architecture o a semantic information retrieval system, called SONCA, will be presented to demonstrate the main idea as well as stimulate the further research on TRSM.
  • Keywords
    data mining; information retrieval systems; ontologies (artificial intelligence); rough set theory; text analysis; SONCA system; TRSM; Web intelligence; clustering; search based on ontologies and compound analytics; semantic indexing; semantic information retrieval system; semantic search; text classification; text databases; text mining; thesaurus generation; tolerance rough set model; Approximation methods; Indexes; Information retrieval; Ontologies; Semantics; Standards; Vectors; Tolerance rough set model; classification; clustering; semantic indexing; semantic search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM International Joint Conferences on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    978-1-4799-2902-3
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2013.189
  • Filename
    6690734