Enriching Retrieval Process for Case Based Reasoning by using Vertical Association Knowledge with Correlation

Abstract

In case-based reasoning (CBR) the most important step is retrieval. The main purpose of the case-based reasoning is to get the cases which are useful to find out the solution for the given problem. For retrieving relevant data the CBR systems mainly uses the similarity knowledge. Most of the retrieving systems use similarity knowledge and association rules for retrieving the required cases. But the existing algorithms strongly rely on similarity knowledge and ignore the other forms of knowledge that can be used to improve the retrieval performance. The well known algorithm Apriori algorithm is used to extract desired relevant cases based on the knowledge system of the association rules with the efficient correlation methods. The goal of this paper is to provide detailed review about retrieving useful cases by using different methods and showing the effectiveness of each algorithm.