A hybrid of sequential rules and collaborative filtering for product recommendation

Duen-Ren Liu*, Chin Hui Lai, Wang Jung Lee

*此作品的通信作者

研究成果: Conference contribution同行評審

4 引文 斯高帕斯(Scopus)

摘要

Customers' purchase behavior may vary over time. Traditional collaborative filtering (CF) methods make recommendations to a target customer based on the purchase behavior of customers whose preferences are similar to those of the target customer; however, the methods do not consider how the customers' purchase behavior may vary over time. Although the sequential rule method considers the sequence of customers' purchase behavior over time, it does not make use of the target customer's purchase data for the current period. To resolve the above problems, this work proposes a novel hybrid recommendation method that combines the segmentation-based sequential rule method with the segmentation-based CF method. Experiment results show that the hybrid method outperforms traditional CF methods.

原文English
主出版物標題Proceedings - The 9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007
頁面211-217
頁數7
DOIs
出版狀態Published - 2007
事件9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007 - Tokyo, Japan
持續時間: 23 7月 200726 7月 2007

出版系列

名字Proceedings - The 9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007

Conference

Conference9th IEEE International Conference on E-Commerce Technology; The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services, CEC/EEE 2007
國家/地區Japan
城市Tokyo
期間23/07/0726/07/07

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