• DocumentCode
    2418840
  • Title

    Association rules mining for name entity recognition

  • Author

    Budi, Indra ; Bressan, Stéphane

  • Author_Institution
    Comput. Sci. Fac., Indonesia Univ., Jakarta, Indonesia
  • fYear
    2003
  • fDate
    10-12 Dec. 2003
  • Firstpage
    325
  • Lastpage
    328
  • Abstract
    We propose a new name entity class extraction method based on association rules. We evaluate and compare the performance of our method with the state of the art maximum entropy method. We show that our method consistently yields a higher precision at a competitive level of recall. This result makes our method particularly suitable for tasks whose requirements emphasize the quality rather than the quantity of results.
  • Keywords
    XML; computational linguistics; data mining; digital libraries; information analysis; information retrieval; maximum entropy methods; pattern recognition; Indonesian digital library; XML; association rule mining; information retrieval; linguistic systems; maximum entropy method; name entity class extraction; name entity recognition; Association rules; Computer science; Costs; Data mining; Decision trees; Dictionaries; Entropy; Information retrieval; Text recognition; Thesauri;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the Fourth International Conference on
  • Print_ISBN
    0-7695-1999-7
  • Type

    conf

  • DOI
    10.1109/WISE.2003.1254504
  • Filename
    1254504