Real-Time Enterprise Ontology Evolution to Aid Effective Clinical Telemedicine with Text Mining and Automatic Semantic Aliasing Support

Authors:
Jackei H. Wong;Wilfred W. Lin;Allan K. Wong
Affiliations:
Department of computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong S.A.R.;Department of computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong S.A.R.;Department of computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong S.A.R.
Venue:
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part II on On the Move to Meaningful Internet Systems
Year:
2008

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Abstract

A novel approach is proposed in this paper to aid real-time enterprise ontology evolution in a continuous fashion. Automatic semantic aliasing (ASA) and text mining (TM) are the two collaborating mechanisms (together known as ASA&TM) that support this approach. The text miner finds new knowledge items from open sources (e.g. the web or given repertoires), and the ASA mechanism associates all the canonical knowledge items in the ontology and those found by text mining via their degrees of similarity. Real-time enterprise ontology evolution makes the host system increasingly smarter because it keeps the host system's ontological knowledge abreast of the contemporary advances. The ASA&TM approach was verified in the Nong's mobile clinics based pervasive TCM (Traditional Chinese Medicine) clinical telemedicine environment. All the experimental results unanimously indicate that the proposed approach is definitively effective for the designated purpose.