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RECSYS
2010
ACM
13 years 7 months ago
Recommending based on rating frequencies
Since the development of the comparably simple neighborhood-based methods in the 1990s, a plethora of techniques has been developed to improve various aspects of collaborative fil...
Fatih Gedikli, Dietmar Jannach
SIGIR
2003
ACM
14 years 24 days ago
Collaborative filtering via gaussian probabilistic latent semantic analysis
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a database of available user preferences. In this ...
Thomas Hofmann
CORR
2007
Springer
95views Education» more  CORR 2007»
13 years 7 months ago
Slope One Predictors for Online Rating-Based Collaborative Filtering
Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with pred...
Daniel Lemire, Anna Maclachlan
TKDD
2010
121views more  TKDD 2010»
13 years 6 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
ISBI
2008
IEEE
14 years 8 months ago
Bayesian non local means-based speckle filtering
In ultrasound (US) imaging, denoising is intended to improve quantitative image analysis techniques. In this paper, a new version of the Non Local (NL) Means filter adapted for US...
Charles Kervrann, Christian Barillot, Pierre Helli...