Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Pointing the way: active collaborative filtering
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
Adaptive web sites: an AI challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Vive la difference! individualised interaction with users
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
The Plight of the Navigator: Solving the Navigation Problem for Wireless Portals
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
METIOREW: An Objective Oriented Content Based and Collaborative Recommending System
Revised Papers from the nternational Workshops OHS-7, SC-3, and AH-3 on Hypermedia: Openness, Structural Awareness, and Adaptivity
Mobile portal personalization: tools and techniques
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
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Content personalisation technologies may hold the key to solving the information overload problem associated with the Internet, by facilitating the development of information services that are customised for the needs of individual users. For example, PTV is an award-winning, Web-based personalised television listings service capable of learning about the viewing habits of individual users and of generating personalised TV guides for these users. This paper describes how PTV has been recently adapted for use on the newgen eration of WAP-enabled Internet devices such as mobile phones - the need for content personalisation is even more acute on WAP devices due to their restricted presentation capabilities.