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158
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AAIM
2008
Springer
208views Algorithms» more  AAIM 2008»
15 years 4 months ago
Large-Scale Parallel Collaborative Filtering for the Netflix Prize
Many recommendation systems suggest items to users by utilizing the techniques of collaborative filtering (CF) based on historical records of items that the users have viewed, purc...
Yunhong Zhou, Dennis M. Wilkinson, Robert Schreibe...
106
Voted
AUSAI
2008
Springer
15 years 4 months ago
Additive Regression Applied to a Large-Scale Collaborative Filtering Problem
Abstract. The much-publicized Netflix competition has put the spotlight on the application domain of collaborative filtering and has sparked interest in machine learning algorithms...
Eibe Frank, Mark Hall
125
Voted
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 2 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...
120
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IIR
2010
15 years 3 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
125
Voted
ICDM
2009
IEEE
188views Data Mining» more  ICDM 2009»
14 years 12 months ago
Binomial Matrix Factorization for Discrete Collaborative Filtering
Matrix factorization (MF) models have proved efficient and well scalable for collaborative filtering (CF) problems. Many researchers also present the probabilistic interpretation o...
Jinlong Wu