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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 7 months ago
Modeling relationships at multiple scales to improve accuracy of large recommender systems
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
Robert M. Bell, Yehuda Koren, Chris Volinsky
ICML
2008
IEEE
14 years 8 months ago
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
Low-rank matrix approximation methods provide one of the simplest and most effective approaches to collaborative filtering. Such models are usually fitted to data by finding a MAP...
Ruslan Salakhutdinov, Andriy Mnih
CORR
2010
Springer
175views Education» more  CORR 2010»
13 years 7 months ago
Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes
Probabilistic matrix factorization (PMF) is a powerful method for modeling data associated with pairwise relationships, finding use in collaborative filtering, computational biolo...
Ryan Prescott Adams, George E. Dahl, Iain Murray
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 7 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
SIGIR
2005
ACM
14 years 20 days ago
An industrial-strength content-based music recommendation system
We present a metadata free system for the interaction with massive collections of music, the MusicSurfer. MusicSurfer automatically extracts descriptions related to instrumentatio...
Pedro Cano, Markus Koppenberger, Nicolas Wack