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inter-purchase time Prediction Based on Deep Learning

Computer Systems Science & Engineering 2022年第8期42卷 493-508页

作者： Ling-Jing Kao Chih-Chou Chiu Yu-Fan Lin Heong Kam Weng Department of Business Management National Taipei University of TechnologyTaipei106Taiwan Digital Transformation Institute Institute for Information IndustryTaipei106Taiwan

inter-purchase time is a critical factor for predicting customer *** the prediction accuracy can exploit consumer’s preference and allow businesses to learn about product or pricing plan weak points,operation issues,as well as customer expectations to proactively reduce reasons for *** remarkable progress has been made,classic statistical models are difficult to capture behavioral characteristics in transaction data because transaction data are dependent and short-,medium-,and long-term data are likely to interfere with each other *** from literature,this study proposed a hybrid inter-purchase time prediction model for customers of on-line ***,the analysis of differences in the purchase behavior of customers has been particularly *** integrated self-organizing map and Recurrent Neural Network technique is proposed to not only address the problem of purchase behavior but also improve the prediction accuracy of inter-purchase *** permutation importance method was used to identify crucial variables in the prediction model and to interpret customer purchase *** performance of the proposed method is evaluated by comparing the prediction with the results of three competing approaches on the transaction data provided by a leading e-retailer in *** study provides a valuable reference for marketing professionals to better understand and develop strategies to attract customers to shorten their inter-purchase times.

关键词： Purchasing behavior e-commerce inter-purchase time self-organizing map recurrent neural network

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