Matrix factorization is a class of collaborative filtering algorithms used in recommender systems. Matrix factorization algorithms work by decomposing...

Bell, Robert; Volinsky, Chris (August 2009). "Matrix Factorization Techniques for Recommender Systems". Computer. 42 (8): 30–37. CiteSeerX 10.1.1.147...

chemometrics, audio signal processing, recommender systems, and bioinformatics. In chemometrics non-negative matrix factorization has a long history under the name...

user-based algorithm, while that of model-based approaches is matrix factorization (recommender systems). A key advantage of the collaborative filtering approach...

1980s, executive information systems (EIS), group decision support systems (GDSS), and organizational decision support systems (ODSS) evolved from the single...

besides content-based filtering, one of two major techniques used by recommender systems. Collaborative filtering has two senses, a narrow one and a more...

(2001). Algorithms for Non-negative Matrix Factorization (PDF). Advances in Neural Information Processing Systems 13: Proceedings of the 2000 Conference...

algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix into a rotation, followed by a rescaling followed by another...

for gene expression modeling, low-rank matrix completion for recommender systems, robust matrix factorization for video surveillance, and concentration...

zero results through the filtering system. Scoring systems – Scoring systems are often found on recommender systems and allow users to rate products for...

MovieLens is a web-based recommender system and virtual community that recommends movies for its users to watch, based on their film preferences using...

algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite. The conjugate gradient...

smaller niches. Not all recommender systems are equal, however, when it comes to expanding the long tail. Some recommenders (i.e. certain collaborative...

when observations are sparse or the matrix is ill-conditioned. In applications such as recommender systems, where matrix entries are discrete (e.g., integer...

on the difficulty of one of three mathematical problems: the integer factorization problem, the discrete logarithm problem or the elliptic-curve discrete...

improving relational matrix factorization in recommender systems" (with Li Pu). In Proceedings of the 7th ACM Conference on Recommender Systems (pp. 41–48). ACM...

Engineering at the University of Minnesota, Twin Cities specializing in recommender systems and online communities. GroupLens also works with mobile and ubiquitous...

Neural Networks. Through his research on PSVM, he demonstrated that matrix factorization can be used to distribute the solver of the Interior Point Method...

Knowledge-aware path-based attentive recommender with interpretability" (PDF). ACM Transactions on Recommender Systems, 3(3), 1-23.{{cite web}}: CS1 maint:...

results in a significant difference in the ranking of the "top-10" most recommended movies for a user. Prizes were based on improvement over Netflix's own...

website Delicious, has shown that collaborative tagging systems exhibit a form of complex systems (or self-organizing) dynamics. Although there is no central...

Intuitionistic logic – Various systems of symbolic logic Kripke semantics – Formal semantics for non-classical logic systems Relevance theory – Theory of...

Algebra Matrix manipulation tools including support for sparse arrays Mathematical function graphing and animation tools Solvers for systems of equations...

Srebro; Jason D. M. Rennie; Tommi S. Jaakkola (2004). Maximum-Margin Matrix Factorization. NIPS. Coates, Adam; Lee, Honglak; Ng, Andrew Y. (2011). An analysis...

classifier regularization (mathematics). The applications include recommender system (communities as hyperedges), image retrieval (correlations as hyperedges)...

item-based, or item-to-item, is a form of collaborative filtering for recommender systems based on the similarity between items calculated using people's ratings...

ALS-based matrix factorization for explicit and implicit feedback datasets", Proceedings of the fourth ACM conference on Recommender systems - Rec Sys...

could be set to match that of ATLAS. To take advantage of recursive factorization, ATLAS provides replacement routines for some LAPACK routines. These...

Filtering, RecSys ‘07 Proceedings of the 2007 ACM Conference on Recommender Systems, 49-56 Bamshad Mobasher, Robin Burke, Chad Williams, and Runa Bhaumik...

algebra, sensor networks, algorithm visualization, bioinformatics, recommender systems, and human–robot interaction. She is Jenkins-Garrett Professor of...