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

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.