Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency

Wong, W., Liu, W. and Bennamoun, M.

In the course of reviewing existing automatic term recognition techniques for applications in ontology learning, we came across four issues which can be improved upon. We proposed a new mechanism that incorporates both statistical and linguistic evidences for the computation of a final weight defined as Termhood (TH) for ranking term candidates. The analysis of the frequency distributions of the term candidates during our initial experiments revealed three advantages for higher quality term recognition.

Cite as: Wong, W., Liu, W. and Bennamoun, M. (2007). Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency. In Proc. Sixth Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia. CRPIT, 70. Christen, P., Kennedy, P. J., Li, J., Kolyshkina, I. and Williams, G. J., Eds. ACS. 47-54.

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