Using vertical association knowledge with correlation for retrieval in case based reasoning

Case-based reasoning (CBR), is the process of solving new problems based on the solutions of similar past problems. The most important step in CBR is reteieval. 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. In this paper the well known algorithm that is 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.