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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