• DocumentCode
    2921683
  • Title

    Enriching non-taxonomic relations extracted from domain texts

  • Author

    Nabila, N.F. ; Mamat, A. ; Azmi-Murad, M.A. ; Mustapha, N.

  • Author_Institution
    Fac. of Sci. & Technol., Univ. Sains Islam Malaysia, Nilai, Malaysia
  • fYear
    2011
  • fDate
    28-29 June 2011
  • Firstpage
    99
  • Lastpage
    105
  • Abstract
    Extracting non-taxonomic relations is one of the important tasks in the construction of ontology from the text. Most of current methods on identification and extraction of non-taxonomic relations is based on predicate representing relationships between two concepts, namely the relation between subject and object that occurs in a sentence. However, the number of relations that has been identified does not properly represent the domain as the methods only identify a portion of the total relations from domain texts. In this paper, we present a method that increases the number of relations extracted and thus properly represent the domain. In this method, all potential relations are first generated and then less significant ones, based on their frequency, are removed. The method has been tested on a collection of texts that described electronic voting machine and the result is encouraging.
  • Keywords
    government data processing; ontologies (artificial intelligence); text analysis; domain text extraction; electronic voting machine; nontaxonomic relation extraction; ontology construction; potential relations; text collection; Association rules; Companies; Frequency domain analysis; Labeling; Object recognition; Ontologies; Non-taxonomic relation; Relation Extraction; Relation Identification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Semantic Technology and Information Retrieval (STAIR), 2011 International Conference on
  • Conference_Location
    Putrajaya
  • Print_ISBN
    978-1-61284-354-4
  • Electronic_ISBN
    978-1-61284-353-7
  • Type

    conf

  • DOI
    10.1109/STAIR.2011.5995772
  • Filename
    5995772