A semantic network representation of personal construct systems

A method is presented for transforming and combining heuristic knowledge gathered from multiple domain experts into a common semantic network representation. Domain expert knowledge is gathered with an interviewing tool based on personal construct theory. The problem of expressing and using a large body of knowledge is fundamental to artificial intelligence and its application to knowledge-based or expert systems. The semantic network is a powerful, general representation that has been used as a tool for the definition of other knowledge representations. Combining multiple approaches to a domain of knowledge may reinforce mutual experiences, information, facts, and heuristics, yet still retain unique, specialist knowledge gained from different experiences. An example application of the algorithm is presented in two separate expert domains. >

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