Abstract
An intelligent hybrid system is proposed. It includes an adaptive human-machine interface and a hybrid case-based reasoning component for knowledge engineering. The adaptive human-machine interface remembers past question and answer scenarios between the system and the end users. It employs a KA-related commonsense base to help user interaction and a housekeeping engine to search and aggregate the data relevant to those the user answered. It discriminates the professional level of the user by the fuzziness of his answers, and provides different interaction patterns for the user accordingly. The hybrid case-based reasoning component hybridizes case-based reasoning, neural networks, fuzzy theory, induction, and knowledge-based reasoning technology. Hybridizing these techniques together properly enhances the robustness of the system, improves the knowledge engineering process, and promotes the quality of the developed knowledge-based systems.
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Hsu, CC., Ho, CS. (1998). An intelligent hybrid system for knowledge acquisition. In: Mira, J., del Pobil, A.P., Ali, M. (eds) Methodology and Tools in Knowledge-Based Systems. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64582-9_781
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DOI: https://doi.org/10.1007/3-540-64582-9_781
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