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WWW
2011
ACM
14 years 4 months ago
2011
ACM
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
ICML
2008
IEEE
15 years 10 months ago
2008
IEEE
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...
WKDD
2010
CPS
15 years 2 months ago
2010
CPS
—Recommender systems apply machine learning techniques for filtering unseen information and can predict whether a user would like a given resource. There are three main types of...
SIGIR
2012
ACM
12 years 12 months ago
2012
ACM
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filterin...
DAWAK
2006
Springer
15 years 1 months ago
2006
Springer
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...