知识的获取、知识库的更新是案例推理技术的应用瓶颈,而许多案例推理系统中的知识库都是静态不变的,满足不了实际问题变化的需要.首先阐述了相关概念,接着提出了一种基于动态数据流挖掘的案例推理模型,其中动态数据流挖掘算法采用改进的数据流聚类算法.通过此模型使用基于动态数据流挖掘的案例推理技术,对数据进行实时挖掘,产生连续、动态的临时案例库,实现知识库的实时更新,从而满足实际问题变化的需要.最后通过该模型在实际中的应用说明其有效性.%The application of case-based reasoning is restricted by the knowledge acquisition and the knowledge base updating. Many knowledge bases in the case-based reasoning system are static and unchangeable, and can not satisfy the change of practical problems.This paper describes the relevant concepts and presents a model of CBR based on dynamic data stream mining,and gives an improved clustering algorithm of data stream.Through this model the system can mine real-time datum, produce continuous, dynamic temporary cases, update the knowledge base in real time and meet the needs of the practical problems.Finally,the application of the model in practice verifies its efficiency.
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