User profile generation reflecting user's temporal preference through web life-log

Authors:
Akinori Nakamura;Nobuhiko Nishio
Affiliations:
Ritsumeikan University;Ritsumeikan University
Venue:
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Year:
2012

Citing 4
Cited 0

Item-based collaborative filtering recommendation algorithms

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PocketLens: Toward a personal recommender system

ACM Transactions on Information Systems (TOIS)
Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions

IEEE Transactions on Knowledge and Data Engineering
Collaborative filtering recommender systems

The adaptive web

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Abstract

We have analyzed logs that which web pages are viewed by users. Information recommendation is one of hot research areas for users activities support. Although many of recommendation systems are eager to match a user's preference, if the user does not want that at that moment, it would be just a noise no matter how much match the preference matches user's preference over all. It is important to understand what the user really wants each of moment timely. Therefore, in this paper, we make use of the following two characteristics for inference user's temporal wish. First is to adapt the degree of user's each interest with time range evolution. Second, web browsing logs related to an activity has been temporarily reinforced. The preliminary result of an algorithm is introduced.