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Monthly Weather Review, ISSN 0027-0644, 11/2012, Volume 140, Issue 11, pp. 3757 - 3782
Journal Article
User Modeling and User-Adapted Interaction, ISSN 0924-1868, 4/2012, Volume 22, Issue 1, pp. 101 - 123
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 12/2007, Volume 16, Issue 12, pp. 2980 - 2991
Journal Article
ACM Transactions on Information Systems (TOIS), ISSN 1046-8188, 01/2004, Volume 22, Issue 1, pp. 143 - 177
The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems ---a personalized information... 
world wide web | e-commerce | predicting user behavior | E-commerce | Predicting user behavior | World wide web | algorithms | performance | experimentation | COMPUTER SCIENCE, INFORMATION SYSTEMS | SYSTEMS | World Wide Web | Models | Algorithms
Journal Article
ACM Transactions on Information Systems (TOIS), ISSN 1046-8188, 11/2012, Volume 30, Issue 4, pp. 1 - 31
The article explores stability as a new measure of recommender systems performance. Stability is defined to measure the extent to which a recommendation... 
collaborative filtering | recommendation stability | performance measures | evaluation of recommender systems | Recommender systems | recommendation accuracy | Measurement | COMPUTER SCIENCE, INFORMATION SYSTEMS | Algorithms | SYSTEMS | ACCEPTANCE | Performance | Reliability | TRUST | Reliability (Engineering) | Research | Artificial intelligence | Analysis
Journal Article
Information Sciences, ISSN 0020-0255, 11/2012, Volume 208, pp. 81 - 104
Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given item. In this paper,... 
Structure learning | Maximum margin | Kernel | Linear operation | Recommender systems | COMPUTER SCIENCE, INFORMATION SYSTEMS | Algorithms | Learning | Kernels | State of the art | Filtration | Filtering | Machine learning
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 08/2010, Volume 11, pp. 2287 - 2322
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm... 
Large scale convex optimization | Netflix prize | Nuclear norm | Collaborative filtering | Spectral regularization | collaborative filtering | large scale convex optimization | spectral regularization | netflix prize | nuclear norm | SELECTION | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Physica A: Statistical Mechanics and its Applications, ISSN 0378-4371, 06/2016, Volume 452, pp. 192 - 208
Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract... 
Information filtering | Random walk | Recommender systems | Complex networks | PHYSICS, MULTIDISCIPLINARY | SYSTEMS | DIVERSITY | PREDICTION | Algorithms | Usage | Recommendations | Networks | Communities | Representations | Internet | Statistical mechanics
Journal Article
Journal Article
ACM Transactions on the Web (TWEB), ISSN 1559-1131, 02/2011, Volume 5, Issue 1, pp. 1 - 33
The technique of collaborative filtering is especially successful in generating personalized recommendations. More than a decade of research has resulted in... 
Collaborative filtering | recommender systems | Recommender systems | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, INFORMATION SYSTEMS | Algorithms | Performance
Journal Article
IEEE Transactions on Signal Processing, ISSN 1053-587X, 07/2011, Volume 59, Issue 7, pp. 3452 - 3457
Journal Article