Keywords
instance-based reasoning shell, intelligent data analysis, data intensive case-based reasoning, intelligent decision support system
Start Date
1-7-2010 12:00 AM
Abstract
In this paper we present a flexible CBR shell for Data-Intensive Case-Based Reasoning Systems which is fully integrated in an Intelligent Data Analysis Tool entitled GESCONDA. The main subgoal of the developed tool is to create a CBR Shell where no fixed domain exists and where letting the expert/user creates (models) his/her own domain. From an abstract point of view, the definition of the CBR can be seen as a methodology composed by four phases and each phase offers different ways to be solved. Then, since the CBR shell is integrated in GESCONDA, it inherits all its functionalities which cover the whole knowledge discovery and data mining process and also, CBR can complement its phases with this functionality. As a result, GESCONDA becomes an intelligent decision support tool which encompasses a number of advantages including domain independence, incremental learning, platform independence and generality.
Providing Intelligent Decision Support Systems with Flexible Data-Intensive Case-Based Reasoning
In this paper we present a flexible CBR shell for Data-Intensive Case-Based Reasoning Systems which is fully integrated in an Intelligent Data Analysis Tool entitled GESCONDA. The main subgoal of the developed tool is to create a CBR Shell where no fixed domain exists and where letting the expert/user creates (models) his/her own domain. From an abstract point of view, the definition of the CBR can be seen as a methodology composed by four phases and each phase offers different ways to be solved. Then, since the CBR shell is integrated in GESCONDA, it inherits all its functionalities which cover the whole knowledge discovery and data mining process and also, CBR can complement its phases with this functionality. As a result, GESCONDA becomes an intelligent decision support tool which encompasses a number of advantages including domain independence, incremental learning, platform independence and generality.
