Knowledge ontology: A method for empirical identification of 'as-is' contextual knowledge

Theresa Edgington, T. S. Raghu, Ajay Vinze

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

In this paper, we consider existing approaches to ontology definition and validation. Popular techniques include the use of domain experts or reliance on formal logic. We consider these contemporary techniques, their motivation and limitations, and then suggest an empirical approach that statistically identifies knowledge ontology within contextual databases using factor analytic techniques. We find that this method improves upon the process of identifying existing, codified knowledge ontology, and that it can be integrated into other methods to improve upon the efficiency of knowledge ontology identification, validation, and evolution. It can facilitate collaboration and inter-organizational progress by providing a common foundation, empirically supported.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Hawaii International Conference on System Sciences
EditorsR.H. Spraque, Jr.
Pages13
Number of pages1
StatePublished - 2005
Event38th Annual Hawaii International Conference on System Sciences - Big Island, HI, United States
Duration: Jan 3 2005Jan 6 2005

Other

Other38th Annual Hawaii International Conference on System Sciences
CountryUnited States
CityBig Island, HI
Period1/3/051/6/05

ASJC Scopus subject areas

  • Engineering(all)

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    Edgington, T., Raghu, T. S., & Vinze, A. (2005). Knowledge ontology: A method for empirical identification of 'as-is' contextual knowledge. In R. H. Spraque, Jr. (Ed.), Proceedings of the Annual Hawaii International Conference on System Sciences (pp. 13)