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A Role-based Model for Asynchronous Knowledge Engineering over the Internet
The expert system is the most popular application of artificial intelligence (AI), and regarded as a new programming development technique. Clinical Decision Support System (CDSS) is one kind of expert system used in the medical field. In comparison with traditional software, the difficulty in the construction of such expert system lays in the knowledge acquisition, that is, the process of “Knowledge Engineering”. Knowledge engineers should guide domain experts to express their “expertise”, chose proper “Inference Engine” for knowledge representation, and yield domain knowledge and experiences in systemized computer language.
The more knowledge-intensive of domain, the more difficult in developing a CDSS, especially in the stage of knowledge acquisition. During the process of knowledge engineering, it is complex, time-consumption and also easy to make mistakes. If there are conflicts or disagreements between experts, it could be very difficult in the integration of knowledge rules, data redundancy, or result in the incomplete knowledge bases.
The development of asynchronous knowledge engineering tool (AKET) could reduce the difficulty of knowledge integration, which not only replace the role of knowledge engineer but also enhance the function effectively.
The study purposed a role-play model of AKET upon preexisting probabilistic inference engine on the web. We constructed two CDSSs by using this model and analyzed the utilities. It proved to be user-friendly, easy-to-use, and user-oriented. The results of this study showed that AKET could resolve the problems occurred in the process of traditional knowledge engineering.