Towards a data-driven ontology engineering framework

Steve Leung, Fuhua Lin, Dunwei Wen

    Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

    Abstract

    The dynamic nature of ontology requires a new methodology to discover the evolving semantics of a particular conceptualization and maintain the novelty of specific ontology with minimal human intervention. This paper posits a conceptual framework that supports a data-driven, iterative, and self-correcting ontology engineering methodology for developing application-oriented and light-weight ontology. The method is being tested and implemented in a work-in-progress intelligent educational system (IES) project that serves an agent-based and ontology-driven academic advising system.

    Original languageEnglish
    Title of host publicationProceedings - ICCE 2008
    Subtitle of host publication16th International Conference on Computers in Education
    Pages87-91
    Number of pages5
    Publication statusPublished - 2008
    Event16th International Conference on Computers in Education, ICCE 2008 - Taipei, Taiwan, Province of China
    Duration: 27 Oct. 200831 Oct. 2008

    Publication series

    NameProceedings - ICCE 2008: 16th International Conference on Computers in Education

    Conference

    Conference16th International Conference on Computers in Education, ICCE 2008
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period27/10/0831/10/08

    Keywords

    • Academic advising
    • Ontology engineering
    • Ontology evolution
    • Text categorization

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