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
Applying case-based reasoning: techniques for enterprise systems
Applying case-based reasoning: techniques for enterprise systems
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Vive la difference! individualised interaction with users
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A case-based approach to knowledge navigation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Speeding up Recommender Systems with Meta-prototypes
SBIA '02 Proceedings of the 16th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Supporting Tourism Culture via CBR
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Personalized Conversational Case-Based Recommendation
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Collaborative Maintenance - A Distributed, Interactive Case-Base Maintenance Strategy
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Diverse Product Recommendations Using an Expressive Language for Case Retrieval
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
A Case-Based Personal Travel Assistant for Elaborating User Requirements and Assessing Offers
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Collaborative Case-Based Reasoning: Applications in Personalised Route Planning
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
A Case-Based Reasoning View of Automated Collaborative Filtering
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Case-Based User Profiling for Content Personalisation
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Automated Collaborative Filtering Applications for Online Recruitment Services
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Collaborative Maintenance in ULYSSES
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
WAP ing the Web: Content Personalisation for WAP-Enabled Devices
AH '00 Proceedings of the International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Learning video preferences from video content
Proceedings of the 8th international workshop on Multimedia data mining: (associated with the ACM SIGKDD 2007)
Expert Systems with Applications: An International Journal
Interface agents personalizing Web-based tasks
Cognitive Systems Research
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In the future digital TV will offer an unprecedented level of programme choice. We are told that this will lead to dramatic increases in viewer satisfaction as all viewing tastes are catered for all of the time. However, the reality may be somewhat different. We have not yet developed the tools to deal with this increased level of choice (for example, conventional TV guides will be virtually useless), and viewers will face a significant and frustrating information overload problem. This paper describes a solution in the form of the PTV system. PTV employs user profiling and information filtering techniques to generate web-based TV viewing guides that are personalised for the viewing preferences of individual users. The paper explains how PTV constructs graded user profiles to drive a hybrid recommendation technique, combining case-based and collaborative information filtering methods. The results of an extensive empirical study to evaluate the quality of PTV's casebased and collaborative filtering strategies are also described