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» Methods for boosting recommender systems
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GFKL
2007
Springer
180views Data Mining» more  GFKL 2007»
14 years 1 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
SIGMOD
2007
ACM
159views Database» more  SIGMOD 2007»
14 years 7 months ago
Boosting topic-based publish-subscribe systems with dynamic clustering
We consider in this paper a class of Publish-Subscribe (pub-sub) systems called topic-based systems, where users subscribe to topics and are notified on events that belong to thos...
Tova Milo, Tal Zur, Elad Verbin
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
12 years 3 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
14 years 8 months ago
Overcoming Incomplete User Models in Recommendation Systems Via an Ontology
Abstract. To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due...
Vincent Schickel-Zuber, Boi Faltings
IWC
2006
44views more  IWC 2006»
13 years 7 months ago
Goal-based structuring in recommender systems
Recommender systems help people to find information that is interesting to them. However, current recommendation techniques only address the user's short-term and long-term i...
Mark van Setten, Mettina Veenstra, Anton Nijholt, ...