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A framework for improving Find Best Marketing Targets using a hybrid Genetic Algorithm and Neural Networks

عنوان مقاله: A framework for improving Find Best Marketing Targets using a hybrid Genetic Algorithm and Neural Networks
شناسه ملی مقاله: KBEI02_028
منتشر شده در دومین کنفرانس بین المللی مهندسی دانش بنیان و نوآوری در سال 1394
مشخصات نویسندگان مقاله:

Behzad Soleimani Neysiani - Department of Software Engineering Faculty of Electrical & Computer Engineering, University of Kashan Kashan, Isfahan, Iran
Nasim Soltani - Department of Software Engineering Allame Naeini Higher Education Institute Naein, Isfahan, Iran
Shima Ghezelbash - Department of IT Management Islamic Azad University of Tehran Tehran, Iran

خلاصه مقاله:
Recently many companies in Iran use tele-marketing to introduce their products. These companies need to detect their best target to following them over seasons and years for more sales. This paper introduces a simple and appropriate method to predict behavior of customers based on the behavior of prior customers. First of all, a dataset of customer action should be made and then preprocessed to reduce its attribute and dimension. Then a neural network will be made based on the selected features to predict sale behavior of customers. Finally an evolutionary algorithm like genetic can be used to find feature of customers who will buy products more. This method evaluated by Portuguese Bank Tele Marketing dataset. Results show that it can simply find best customers in this case study. It’s highly recommended to companies use this method to reduce their marketing costs and have better performance.

کلمات کلیدی:
Tele Marketing, Bank, Best Targets, Prediction, Artificial Intelligence Techniques, Dimension Reduction, Rapid Miner, Neural Networks, Evolutionary Algorithms, Genetic Algorithm

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/553078/