Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Restricted Boltzmann machines for collaborative filtering
Proceedings of the 24th international conference on Machine learning
ACM SIGKDD Explorations Newsletter - Special issue on visual analytics
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Computational Complexity Reduction for Factorization-Based Collaborative Filtering Algorithms
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
Recommending new movies: even a few ratings are more valuable than metadata
Proceedings of the third ACM conference on Recommender systems
Fast als-based matrix factorization for explicit and implicit feedback datasets
Proceedings of the fourth ACM conference on Recommender systems
Integrating OLAP and recommender systems: an evaluation perspective
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Learning multiple models for exploiting predictive heterogeneity in recommender systems
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Temporal rating habits: a valuable tool for rating discrimination
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Kernel-Mapping Recommender system algorithms
Information Sciences: an International Journal
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
Active spectral clustering via iterative uncertainty reduction
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting time contexts in collaborative filtering: an item splitting approach
Proceedings of the 3rd Workshop on Context-awareness in Retrieval and Recommendation
Learning descriptive visual representation by semantic regularized matrix factorization
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Matrix Factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this work, we propose several matrix factorization approaches with improved prediction accuracy. We introduce a novel and fast (semi)-positive MF approach that approximates the features by using positive values for either users or items. We describe a momentum-based MF approach. A transductive version of MF is also introduced, which uses information from test instances (namely the ratings users have given for certain items) to improve prediction accuracy. We describe an incremental variant of MF that efficiently handles new users/ratings, which is crucial in a real-life recommender system. A hybrid MF--neighbor-based method is also discussed that further improves the performance of MF. The proposed methods are evaluated on the Netflix Prize dataset, and we show that they can achieve very favorable Quiz RMSE (best single method: 0.8904, combination: 0.8841) and running time.