• DocumentCode
    2326440
  • Title

    Ambiguity in text mining

  • Author

    Al Fawareh, H.M. ; Jusoh, Shaidah ; Osman, Wan Rozaini Sheikh

  • Author_Institution
    Grad. Dept. of Comput. Sci., Univ. Utara Malaysia, Kedah
  • fYear
    2008
  • fDate
    13-15 May 2008
  • Firstpage
    1172
  • Lastpage
    1176
  • Abstract
    Text Mining tasks include text categorization, text clustering, concept/entity extraction, document summarization, and entity relation modeling. In this paper, the focus is given to concept/entity extraction only. The major challenging issue in extracting concept/entity from texts is natural language words are always ambiguous. Up to now, not much research in text mining especially in concept/entity extraction has focused on the ambiguity problem. This paper addresses ambiguity issues in natural language texts, and presents a new technique for resolving ambiguity problem in extracting concept/entity from texts. The technique is developed by applying possibility theory, fuzzy set, and knowledge about the context to lexical semantics.
  • Keywords
    entity-relationship modelling; information retrieval; natural language processing; text analysis; ambiguity problem; concept extraction; document summarization; entity extraction; entity relation modeling; natural language words; text categorization; text clustering; text mining; Data mining; Fuzzy set theory; Fuzzy sets; Humans; Natural languages; Possibility theory; Text categorization; Text mining; Text processing; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Communication Engineering, 2008. ICCCE 2008. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-1691-2
  • Electronic_ISBN
    978-1-4244-1692-9
  • Type

    conf

  • DOI
    10.1109/ICCCE.2008.4580791
  • Filename
    4580791