A recommendation method considering users' time series contexts

Authors:
Kenta Oku;Shinsuke Nakajima;Jun Miyazaki;Shunsuke Uemura;Hirokazu Kato
Affiliations:
Nara Institute of Science and Technology, Ikoma City, Nara, Japan;Kyoto Sangyo University, Motoyama, Kamigamo, Kita-Ku, Kyoto-City, Japan;Nara Institute of Science and Technology, Ikoma City, Nara, Japan;Nara Sangyo University, Sango-cho, Ikoma-gun, Nara, Japan;Nara Institute of Science and Technology, Ikoma City, Nara, Japan
Venue:
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
Year:
2009

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Abstract

This paper proposes a recommendation method considering users' time series contexts which are situations that have occurred / will occur in the past/future. There are some recommendation methods that provide information suitable for users' action patterns as the recommendation methods considering them. These methods provide information referring to the other users that have a similar action pattern to that of an active user. However, since a user's action pattern changes depending on the user's contexts, the methods need to refer to the other users' action patterns related to the current user's contexts. In this paper, we propose a recommendation method considering the user's time series contexts considering that the user's action pattern changes depending on the user's contexts.