GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Communications of the ACM
Huffman coding with unequal letter costs
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
The Psychology of Human-Computer Interaction
The Psychology of Human-Computer Interaction
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Latent Class Models for Collaborative Filtering
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
A POMDP formulation of preference elicitation problems
Eighteenth national conference on Artificial intelligence
SUPPLE: automatically generating user interfaces
Proceedings of the 9th international conference on Intelligent user interfaces
Fast Polyhedral Adaptive Conjoint Estimation
Marketing Science
Improving proactive information systems
Proceedings of the 10th international conference on Intelligent user interfaces
Proceedings of the 10th international conference on Intelligent user interfaces
The future of user interface design tools
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Planning for stream processing systems
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
How to best characterize the personalization construct for e-services
Expert Systems with Applications: An International Journal
Rule based GUI modification and adaptation
CompSysTech '09 Proceedings of the International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing
Rule based framework for intelligent GUI adaptation
Proceedings of the 12th International Conference on Computer Systems and Technologies
Electronic Commerce Research and Applications
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Interface personalization can improve a user's performance and subjective impression of interface quality and responsiveness. Personalization is difficult to implement as it requires an accurate model of a user's intentions and a formal model of how an interface meets a user's need. We present a novel model for tractable inference of consumer intentions in the context of grocery shopping. The model makes unique use of a priori temporal relations to simplify inference. We then present a simple interface generation framework that was inspired by viewing user interface interaction as a channel coding problem. The resulting model defines a simplified but clear notion of a user's utility for an interface. We demonstrate the effectiveness of the research prototype on some simple data, and explain how the model can be augmented with richer user modeling to create a deployable application.