DocumentCode :
3206226
Title :
A Hybrid of Sequential Rules and Collaborative Filtering for Product Recommendation
Author :
Liu, Duen-Ren ; Lai, Chin-Hui ; Lee, Wang-Jung
Author_Institution :
Nat. Chiao Tung Univ., Hsinchu
fYear :
2007
fDate :
23-26 July 2007
Firstpage :
211
Lastpage :
220
Abstract :
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.
Keywords :
consumer behaviour; groupware; information filtering; information filters; knowledge based systems; purchasing; collaborative filtering; customer purchase behavior; product recommendation; segmentation-based CF method; segmentation-based sequential rule method; Collaboration; Collaborative work; Information filtering; Information filters; Information management; Motion pictures; Recommender systems; Taxonomy; Time factors; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Commerce Technology and the 4th IEEE International Conference on Enterprise Computing, E-Commerce, and E-Services, 2007. CEC/EEE 2007. The 9th IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7695-2913-5
Type :
conf
DOI :
10.1109/CEC-EEE.2007.6
Filename :
4285217
Link To Document :
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