Analyzing domain expertise by considering variants of knowledge in multiple time scales

  • Authors:

  • Jun-Ming Chen;Gwo-Haur Hwang;Gwo-Jen Hwang;Carol H. C. Chu

  • Affiliations:

  • Information Management Department, National Chi Nan University, Puli, Nantou, Taiwan, R.O.C.;Information Management Department, Ling Tung College, Taichung, Taiwan, R.O.C;Department of Information and Learning Technology, National University of Tainan, Tainan, Taiwan, R.O.C.;Information Management Department, National Chi Nan University, Puli, Nantou, Taiwan, R.O.C.

  • Venue:
  • KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
  • Year:
  • 2005

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Abstract

Knowledge acquisition is known to be a critical bottleneck in building expert systems. In past decades, various methods and systems have been proposed to efficiently elicit expertise from domain experts. However, in building a medical expert system, disease symptoms are usually treated as time-irrelevant attributes, such that much important information is abandoned and hence the performance of the constructed expert systems is significantly affected. To cope with this problem, in this paper, we propose a time scale-oriented approach to eliciting medical knowledge from domain experts. The novel approach takes the time scale into consideration, such that the variant of disease symptoms in different time scales can be precisely expressed. An application to the development of a medical expert system has depicted the superiority of our approach.