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KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 6 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
ICIP
2010
IEEE
13 years 3 months ago
Global motion temporal filtering for in-loop deblocking
One of the most severe problems in hybrid video coding is its block-based approach, which leads to distortions called blocking artifacts. These artifacts affect not only the subje...
Alexander Glantz, Andreas Krutz, Thomas Sikora
GFKL
2007
Springer
180views Data Mining» more  GFKL 2007»
13 years 12 months ago
Content-based Dimensionality Reduction for Recommender Systems
Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommen...
Panagiotis Symeonidis
STAIRS
2008
169views Education» more  STAIRS 2008»
13 years 7 months ago
Probabilistic Association Rules for Item-Based Recommender Systems
Since the beginning of the 1990's, the Internet has constantly grown, proposing more and more services and sources of information. The challenge is no longer to provide users ...
Sylvain Castagnos, Armelle Brun, Anne Boyer
IUI
2010
ACM
14 years 2 months ago
Personalized news recommendation based on click behavior
Online news reading has become very popular as the web provides access to news articles from millions of sources around the world. A key challenge of news websites is to help user...
Jiahui Liu, Peter Dolan, Elin Rønby Pederse...