Proposal and evaluation of a recommendation technique that considers the context of product purchases

Authors:
Tsuyoshi Takayama;Tetsuo Ikeda;Hiroshi Oguma;Ryosuke Miura;Yoshitoshi Murata;Nobuyoshi Sato
Affiliations:
Graduate School of Software and Information Science, Iwate Prefectural University, Iwate, Japan;School of Administration and Informatics, University of Shizuoka, Shizuoka, Shizuoka, Japan;Mainichi Communications Inc., Chiyoda, Tokyo, Japan;Consulting Group III, FUJITSU Research Institute, Minato, Tokyo, Japan;Graduate School of Software and Information Science, Iwate Prefectural University, Iwate, Japan;Graduate School of Software and Information Science, Iwate Prefectural University, Iwate, Japan
Venue:
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
Year:
2009

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Abstract

We propose here in a technique for product recommendation in E-commerce by considering the context of product purchases, and verify the effectiveness of the technique through an evaluation experiment. Researchers have been aggressively studying techniques that can be used by stores to recommend to customers products that have relatively high purchase potential. Collaborative filtering is representative of conventional techniques. However, the collaborative filtering technique is based on the hypothesis that similar customers purchase similar products, and the context of product purchases is not considered in full. In the present study, a context matrix by which to manage the context history of product purchases is proposed. The results of an evaluation experiment reveal that our proposition is useful.