Journal of Information Technology Applications and Management

  • 제24권1호
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  • Pages.111-128
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  • 2017
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  • 1598-6284(pISSN)
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  • 2508-1209(eISSN)
한국데이터전략학회 (Korea Data Strategy Society)
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반복 구매제품의 재구매시기 예측을 위한 다층퍼셉트론(MLP) 모형과 순환신경망(RNN) 모형의 성능비교

Comparison of Performance between MLP and RNN Model to Predict Purchase Timing for Repurchase Product

  • Song, Hee Seok (Department of Global IT Business in Hannam University)
  • 투고 : 2016.12.03
  • 심사 : 2017.02.08
  • 발행 : 2017.03.31
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초록

Existing studies for recommender have focused on recommending an appropriate item based on the customer preference. However, it has not yet been studied actively to recommend purchase timing for the repurchase product despite of its importance. This study aims to propose MLP and RNN models based on the only simple purchase history data to predict the timing of customer repurchase and compare performances in the perspective of prediction accuracy and quality. As an experiment result, RNN model showed outstanding performance compared to MLP model. The proposed model can be used to develop CRM system which can offer SMS or app based promotion to the customer at the right time. This model also can be used to increase sales for repurchase product business by balancing the level of order as well as inducing repurchase of customer.

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참고문헌

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