GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Getting to know you: learning new user preferences in recommender systems
Proceedings of the 7th international conference on Intelligent user interfaces
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
A POMDP formulation of preference elicitation problems
Eighteenth national conference on Artificial intelligence
Active learning with statistical models
Journal of Artificial Intelligence Research
Latent class models for collaborative filtering
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A Bayesian approach toward active learning for collaborative filtering
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Learning Parts-Based Representations of Data
The Journal of Machine Learning Research
Selectively acquiring ratings for product recommendation
Proceedings of the ninth international conference on Electronic commerce
SONAR: A Semantically Empowered Financial Search Engine
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Regret-based optimal recommendation sets in conversational recommender systems
Proceedings of the third ACM conference on Recommender systems
Active learning driven by rating impact analysis
Proceedings of the fourth ACM conference on Recommender systems
Functional matrix factorizations for cold-start recommendation
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Proceedings of the fifth ACM conference on Recommender systems
Collaborative filtering using associative neural memory
ITWP'03 Proceedings of the 2003 international conference on Intelligent Techniques for Web Personalization
A probe prediction approach to overlay network monitoring
Proceedings of the 7th International Conference on Network and Services Management
Exploiting the characteristics of matrix factorization for active learning in recommender systems
Proceedings of the sixth ACM conference on Recommender systems
Efficiently learning the preferences of people
Machine Learning
Learning multiple-question decision trees for cold-start recommendation
Proceedings of the sixth ACM international conference on Web search and data mining
Active learning and search on low-rank matrices
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Collaborative filtering (CF) allows the preferences of multiple users to be pooled to make recommendations regarding unseen products. We consider in this paper the problem of online and interactive CF: given the current ratings associated with a user, what queries (new ratings) would most improve the quality of the recommendations made? We cast this in terms of expected value of information (EVOI); but the online computational cost of computing optimal queries is prohibitive. We show how ofline prototyping and computation of bounds on EVOI can be used to dramatically reduce the required online computation. The framework we develop is general, but we focus on derivations and empirical study in the specific case of the multiplecause vector quantization model.