• DocumentCode
    2727814
  • Title

    Automatic Taxonomy Extraction Using Google and Term Dependency

  • Author

    Makrehchi, Masoud ; Kamel, Mohamed S.

  • fYear
    2007
  • fDate
    2-5 Nov. 2007
  • Firstpage
    321
  • Lastpage
    325
  • Abstract
    An automatic taxonomy extraction algorithm is proposed. Given a set of terms or terminology related to a subject domain, the proposed approach uses Google page count to estimate the dependency links between the terms. A taxonomic link is an asymmetric relation between two concepts. In order to extract these directed links, neither mutual information nor normalized Google distance can be employed. Using the new measure of information theoretic inclusion index, term dependency matrix, which represents the pair-wise dependencies, is obtained. Next, using a proposed algorithm, the dependency matrix is converted into an adjacency matrix, representing the taxonomy tree. In order to evaluate the performance of the proposed approach, it is applied to several domains for taxonomy extraction.
  • Keywords
    Data mining; Databases; Information systems; Machine intelligence; Matrix converters; Ontologies; Pattern analysis; Semantic Web; Taxonomy; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, IEEE/WIC/ACM International Conference on
  • Conference_Location
    Fremont, CA
  • Print_ISBN
    978-0-7695-3026-0
  • Type

    conf

  • DOI
    10.1109/WI.2007.37
  • Filename
    4427111