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Case retrieval optimization of Casebased reasoning through Knowledgeintensive Similarity measures

Author(s): Surjeet Dalal | Dr. Vijay Athavale | Keshav Jindal

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: 34;
Issue: 3;
Start page: 12;
Date: 2011;
Original page

Keywords: Case-based Reasoning | Case retrieval | Similarity measures | Knowledge-intensive similarity measures | myCBR

Case based reasoning has become the emerging field of Artificial Intelligence area. It is mostly used in designing the real time application having the decision support capability. It reassembles with human reasoning approach. This reasoning approach contains four phases. It stores the solution of past problems faced in form the case in its case base. In this paper we have discussed about the case retrieval phase of case based reasoning approach. All efficiency of the CBR system depends on the case retrieval process. There are various strategies are used in this phase of case based reasoning. Nearest neighbour and Induction retrieval algorithms are discussed. These algorithms are very simple but inefficient in larger case base and incomplete case. In this paper we will discuss KnowledgeIntensive Similarity measure retrieval strategies for the case base reasoning system and model the knowlededgeintensive similarity measure by using myCBR tool. The basic purpose of our work is to over the bottlenecks of other retrieval strategies.
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