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CCIA
2005
Springer
13 years 10 months ago
Modelling the Human Values Scale in Recommender Systems: A first approach
The objective of this paper is two-fold. The first is to develop a methodology capable of extracting the Human Values Scale (HVS) from the user, with reference to his/her objective...
Javier Guzmán, Gustavo González, Jos...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
14 years 4 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
14 years 5 months 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
STAIRS
2008
169views Education» more  STAIRS 2008»
13 years 5 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
RECSYS
2010
ACM
13 years 4 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street