2011 · 372 citations · 19 references
ComputingComputer ScienceMachine LearningPredictive AnalyticsRecommender SystemsCollaborative FilteringOnline RecommendationRecommendation EvaluationRecommendation SystemsImplicit FeedbackImplicit Feedback RecommendationPersonalized RecommendationPositive FeedbackRating PredictionReal-time RecommendationRecommendation EnginesScalable Recommendation Systems
MyMediaLite is a fast and scalable, multi-purpose library of recommender system algorithms, aimed both at recommender system researchers and practitioners. It addresses two common scenarios in collaborative filtering: rating prediction (e.g. on a scale of 1 to 5 stars) and item prediction from positive-only implicit feedback (e.g. from clicks or purchase actions). The library offers state-of-the-art algorithms for those two tasks. Programs that expose most of the library's functionality, plus a GUI demo, are included in the package. Efficient data structures and a common API are used by the implemented algorithms, and may be used to implement further algorithms. The API also contains methods for real-time updates and loading/storing of already trained recommender models.
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Matrix Factorization Techniques for Recommender Systems
Yehuda Koren, Robert Bell, Chris Volinsky · Computer · 2009 · 11.7K citations
BPR: Bayesian Personalized Ranking from Implicit Feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner et al. · arXiv (Cornell University) · 2012 · 4.4K citations · Full text
Collaborative Filtering for Implicit Feedback Datasets
Yifan Hu, Yehuda Koren, Chris Volinsky · 2008 · 3.2K citations
Computing, Data Science, Data Mining +16