Ontology-based automatic classification for Web pages: Design, implementation and evaluation

  • R. Prabowo
  • , M. Jackson
  • , P. Burden
  • , H. D. Knoell

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

    23 Citations (Scopus)

    Abstract

    In recent years, we have witnessed continual growth in the use of ontologies in order to provide a mechanism to enable machine reasoning. This paper describes an automatic classifier, which focuses on the use of ontologies for classifying Web pages with respect to Dewey Decimal Classification (DDC) and Library of Congress Classification (LCC) schemes. Firstly, we explain how these ontologies can be built in a modular fashion, and mapped into DDC and LCC. Secondly, we propose the formal definition of a DDC-LCC and an ontology-classification-scheme mapping. Thirdly, we explain the way the classifier uses these ontologies to assist classification. Finally, an experiment in which the accuracy of the classifier was evaluated is presented. The experiment shows that our approach results an improved classification in terms of accuracy. This improvement, however, comes at a cost in a low coverage ratio due to incompleteness of the ontologies used.

    Original languageEnglish
    Title of host publicationWISE 2002 - Proceedings of the 3rd International Conference on Web Information Systems Engineering
    EditorsWee Keong Ng, Tok Wang Ling, Angela Goh, Umeshwar Dayal, Elisa Bertino
    Number of pages10
    PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
    Publication date2002
    Pages182-191
    Article number1181655
    ISBN (Print)0769517668 , 9780769517667
    DOIs
    Publication statusPublished - 2002
    Event3rd International Conference on Web Information Systems Engineering - WISE 2002 - Singapore, Singapore
    Duration: 12.12.200214.12.2002
    Conference number: 3

    Research areas and keywords

    • Informatics

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