روش طبقه بندی مشتری بر اساس مورد برای بازاریابی مستقیم
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|2396||2002||6 صفحه PDF||سفارش دهید||4500 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Expert Systems with Applications, Volume 22, Issue 2, February 2002, Pages 163–168
Case-based reasoning (CBR) shows significant promise for improving the effectiveness of complex and unstructured decision making. CBR is both a paradigm for computer-based problem-solvers and a model of human cognition. However the design of appropriate case retrieval mechanisms is still challenging. This paper presents a genetic algorithm (GA)-based approach to enhance the case-matching process. A prototype GA–CBR system used to predict customer purchasing behavior is developed and tested with real cases provided by one worldwide insurance direct marketing company, Taiwan branch. The results demonstrate better prediction accuracy over the results from the regression-based CBR system. Also an optimization mechanism is integrated into the classification system to reveal those customers most likely and most unlikely customers to purchase insurance.