657 / 2024-04-30 15:28:46
Price-aware enhanced dynamic recommendation based on deep learning
Price preference,Dynamic preference,online consumer reviews,Deep learning,Personalized recommendation
摘要待审
GuoWenhao / Tianjin University
TianJin / Tianjin University
FengHaiyang / Tianjin University
LiMinqiang / Tianjin University
Price is one of the essential elements influencing consumer purchase behavior. Like consumers’ preferences in products, their price preferences also dynamically change over time. However, dynamic price preferences haven’t been fully considered in existed recommendation studies. In this study, we propose a deep learning-based dynamic recommendation model by considering consumers’ dynamic preferences in both product and price. We specially design a review-and-rating-based sequence generator to select products whose prices the consumers are satisfied with to form the new purchase sequence. We also develop a multi-level attention mechanism in the transformer layer to explore the correlations between consumers’ price choices and to combine the price preferences with the product preferences. Experimental results show the proposed model outperforms the state-of-the-art models on some real-world datasets. Our findings can help retailers understand consumers’ price preferences and make informed decisions related to pricing, discounting, and bundle sales strategies.

 
重要日期
  • 会议日期

    06月28日

    2024

    07月01日

    2024

  • 07月01日 2024

    注册截止日期

主办单位
中国科学技术大学
协办单位
管理科学与工程学会
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