【摘要】 针对专家系统中知识自动获取的瓶颈问题,从专家系统自身的潜在规律(机理)出发来改变知识发现的固有流程、形成新的知识发现过程模型和构建基于认知的知识自动获取机制,并利用T型协调器,根据基础知识库中的"知识短缺"自动地启发定向挖掘知识的途径,有效地克服领域专家的自身局限,而且做到只对那些有可能成为新知识的假设进行评价,最大限度地减少评价工作量,由此形成知识自动获取机制。这一机制在很大程度上解决了智能系统中的知识自动获取的瓶颈问题。更多还原

【Abstract】 The research was carried out to solve the bottleneck problem of automatic acquisition of knowledge in expert systems. Starting from the potential law (mechanism) of an expert system itself, the study tried to change the inherent knowledge discovery process, form the new knowledge discovery process model, and build a cognition-based automatic knowledge acquisition mechanism. Simultaneously, by using the T-coordinator, it automatically started the directed excavation of knowledge, according to the knowledge shortages of the basic knowledge, to effectively overcome the limitations that could become the new knowledge and minimize the workload of evaluation, thus forming a mechanism for automatic acquisition of knowledge. This mechanism can solve, to a great extent, the bottleneck problem of automatic acquisition of knowledge in intelligent systems.更多还原