• DocumentCode
    2606205
  • Title

    Mining term association rules for automatic global query expansion: methodology and preliminary results

  • Author

    Wei, Jie ; Bressan, Stéphane ; Ooi, Beng Chin

  • Author_Institution
    Sch. of Comput., Nat. Univ. of Singapore, Singapore
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    366
  • Abstract
    The authors are looking at the mining of association between terms for the automatic expansion of queries. The technique used for the discovery of the associations is association rule mining (R. Agrawal et al., 1996). The technique proposed is more flexible than previous techniques based on term co-occurrence since it takes into account not only the co-occurrence frequency but also the confidence and direction of the association rules. We have been able to consistently improve the effectiveness of the retrieval over the set of 48 test queries on the Associated Press 1990 news wires corpus of the TREC4 benchmark by query expansion using term association rules
  • Keywords
    data mining; document handling; query processing; Associated Press 1990 news wires corpus; TREC4 benchmark; association rule mining; automatic global query expansion; co-occurrence frequency; term association rule mining; term co-occurrence; test queries; Association rules; Benchmark testing; Data mining; Frequency; Government; Information retrieval; Ontologies; Search engines; Thesauri; Wires;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems Engineering, 2000. Proceedings of the First International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-0577-5
  • Type

    conf

  • DOI
    10.1109/WISE.2000.882414
  • Filename
    882414