COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Communications of the ACM
Malicious Omissions and Errors in Answers to Membership Queries
Machine Learning
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Efficient search for approximate nearest neighbor in high dimensional spaces
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
An optimal algorithm for approximate nearest neighbor searching
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Machine Learning
Machine Learning
Collaborative Filtering Using Weighted Majority Prediction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Approximation algorithms for combinatorial problems
Journal of Computer and System Sciences
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
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We consider the problem of determining which of a set of experts has tastes most similar to a given user by asking the user questions about his likes and dislikes. We describe a simple and fast algorithm for a theoretical model of this problem with a provable approximation guarantee, and prove that solving the problem exactly is NP-Hard.