15 search results - page 3 / 3 » Item Preference Parameters from Grouped Ranking Observations |
SIGIR
2003
ACM
14 years 3 months ago
2003
ACM
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 ...
KDD
2009
ACM
14 years 10 months ago
2009
ACM
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
SCIA
2009
Springer
14 years 4 months ago
2009
Springer
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
SDM
2012
SIAM
12 years 5 days ago
2012
SIAM
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
KDD
2007
ACM
14 years 10 months ago
2007
ACM
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...