A study on case-based reasoning using generalized association rules mining

被引：0
|
作者：
Kim, S [1 ]
He, PL [1 ]
机构：
[1] Tianjin Univ, Sch Elect & Informat Engn, Tianjin 300072, Peoples R China
来源：
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词：
case-based reasoning; association rule; data mining; expert system;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Case-Based Reasoning (CBR) is a method for solving new problem similar with it using the past solving problem experience. A case can be seen as a complex object that contains at least a problem description and a solution (i.e., a conditionality and a consequence). Between the conditionality and its consequence a strong association is existed. The focus of this paper is to describe a method discovering usable rules among case history by using the generalized association rule algorithm. Emphasis placed on approaching association rule mining for discovering rules existing in case history.
引用
收藏
页码：1982 / 1986
页数：5
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