Kosuke Takano
ABSTRACT
In social media, it is important to build a community that includes people who share similar interests and purposes to foster further interaction and communication. In this study, we present a user profile construction method based on a time series of user preferences to allow the recommendation of appropriate people for the community. This method extracts user preferences as time series data by capturing the user's information browsing behavior in three information spaces: (1) a Web document information space, (2) an augmented reality information space, and (3) an interaction information space with applications for mobile devices. Our proposed method suggests potential members of a clique thus providing opportunities for users of social media to notice the implicit interests associated with other users based on their browsing behavior from the past to the current state, as well as to encourage social communication and relationships.
- Bilenko, M. and White, R. W. 2008. Mining the Search Trails of Surfing Crowds: Identifying Relevant Websites from User Activity. In Proceedings of the 17th International World Wide Web Conference. WWW'08. 51--60. Google Scholar
Digital Library
- Burklen, S., Marron, P. J., Fritsch, S. and Rothermel, K. 2005. User Centric Walk: An Integrated Approach for Modeling the Browsing Behavior of Users on the Web. In Proceedings of the 38th Annual Symposium on Simulation, 149--159. Google ScholarDigital Library
- Marcialis, I. and Vita, E. D. 2008. SEARCHY: An Agent to Personalize Search Results. In Proceedings of the 3rd International Conference on Internet and Web Applications and Services. 512--517. Google ScholarDigital Library
- Spalteholz, L., Li, K. F. and Livingston, N. 2008. KeySurf: A Character Controlled Browser for People with Physical Disabilities. In Proceedings of the 17th International World Wide Web Conference. WWW'08. 31--39. Google ScholarDigital Library
Index Terms
- The framework of a people recommender based on a time series of user preferences
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