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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
10 years 12 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
WWW
2009
ACM
11 years 7 days ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel
ICMCS
2006
IEEE
167views Multimedia» more  ICMCS 2006»
10 years 5 months ago
Mining Relationship Between Video Concepts using Probabilistic Graphical Models
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. These semantic concepts do not exist in isolatio...
Rong Yan, Ming-yu Chen, Alexander G. Hauptmann
SAINT
2005
IEEE
10 years 5 months ago
On Scalable Modeling of TCP Congestion Control Mechanism for Large-Scale IP Networks
In this paper, we propose an analytic approach of modeling a closed-loop network with multiple feedback loops using fluid-flow approximation. Specifically, we model building bl...
Hiroyuki Ohsaki, Juñya Ujiie, Makoto Imase
TKDD
2010
121views more  TKDD 2010»
9 years 10 months ago
Factor in the neighbors: Scalable and accurate collaborative filtering
Recommender systems provide users with personalized suggestions for products or services. These systems often rely on Collaborating Filtering (CF), where past transactions are ana...
Yehuda Koren
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