基于动态数据流挖掘的案例推理及其应用  

Case based reasoning and application based on dynamic data stream mining

作　　者：戴奇波[1,2] 倪志伟[1,2] 王超[1,2] 姜苗[1,2] 

机构地区：[1]合肥工业大学管理学院,合肥230009 [2]过程优化与智能决策教育部重点实验室,合肥230009

出　　处：《计算机工程与应用》2011年第19期31-34,共4页Computer Engineering and Applications

基　　金：国家高技术研究发展计划(863)No.2007AA04Z116;国家自然科学基金(No.70871033)~~

摘　　要：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.

关 键 词：数据流 案例推理 聚类 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]