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Context-aware collaborative filtering system: predicting the user's preferences in ubiquitous computing

Published:02 April 2005Publication History

ABSTRACT

In this paper I propose a context-aware collaborative filtering system that can predict a user's preference in different context situations based on past user-experiences. The system uses what other like-minded users have done in similar context to predict a user's preference towards an item in the current context.

References

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  2. John S. Breese, David Heckerman, and Carl Kadie. Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pages 43--52, July 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. Petrone L. Ardissono, A. Goy. INTRIGUE: personalized recommendation of tourist attractions for desktop and handset devices. Applied Artificial Intelligence, 17(8-9):687--714, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  4. Mark van Setten, Stanislav Pokraev, and Johan Koolwaaij. Context-Aware Recommendations in the Mobile Tourist Application COMPASS. In Adaptive Hypermedia 2004, volume 3137 ofLNCS, pages 235--244, August 2004.Google ScholarGoogle Scholar

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  1. Context-aware collaborative filtering system: predicting the user's preferences in ubiquitous computing

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    • Published in

      cover image ACM Conferences
      CHI EA '05: CHI '05 Extended Abstracts on Human Factors in Computing Systems
      April 2005
      1358 pages
      ISBN:1595930027
      DOI:10.1145/1056808

      Copyright © 2005 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 2 April 2005

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      Overall Acceptance Rate6,164of23,696submissions,26%

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