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

Author

Kim, Sungnam ; He, Pi-Lian

Author_Institution

Sch. of Electron. & Inf. Eng., Tianjin Univ., China

Volume

4

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

1982

Abstract

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 conditionally 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.

Keywords

case-based reasoning; data mining; expert systems; generalisation (artificial intelligence); problem solving; transaction processing; CBR method; case transaction databases; case-based reasoning; expert system; generalized association rule mining; problem solving; rule discovery; Association rules; Data mining; Electronic mail; Helium; History; Humans; Minerals; Predictive models; Problem-solving; Software engineering; Association rule; Case-Based Reasoning; Data Mining; Expert System;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527270

Filename

1527270