Problem New Case RETRIEVE Learned Case Retrieved Cases New Case RETAIN Tested/ Repaired Case Case-Base REVISE Solved Case REUSE

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Case-based reasoning(cbr) is a problem solving technique that is quite simple to implement in general, but often handles complex and unstructured decision making problems very effectively. Thus, it has been applied to various problem-solving areas including manufacturing, finance and marketing. Nonetheless, it is never easy to design effective CBR systems because they have several factors for design including issues on 'combining similar cases'. This study proposes a novel CBR model, which explores similar cases in an innovative way. Conventional CBR models determine similar cases according to fixed number of neighbors to combine, or relative similarity ratios. However, our model selects similar cases based on similarity threshold - an absolute value ranging from 0 to 1 - and coverage. To validate the usefulness of our model, we applied it to a case for target marketing of an Internet shopping mall in Korea. As a result, we found that our model might be applied to find appropriate prospects for target marketing in an effective way. *Full-time Instructor, Dept. of Business Administration, SungShin Women's University