Sciweavers

10 search results - page 2 / 2
» LARS: A learning algorithm for rewriting systems
Sort
View
WWW
2010
ACM
13 years 12 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
WSDM
2010
ACM
214views Data Mining» more  WSDM 2010»
14 years 2 months ago
Pairwise Interaction Tensor Factorization for Personalized Tag Recommendation
Tagging plays an important role in many recent websites. Recommender systems can help to suggest a user the tags he might want to use for tagging a specific item. Factorization mo...
Steffen Rendle, Lars Schmidt-Thieme
WSDM
2012
ACM
352views Data Mining» more  WSDM 2012»
12 years 14 days ago
Multi-relational matrix factorization using bayesian personalized ranking for social network data
A key element of the social networks on the internet such as Facebook and Flickr is that they encourage users to create connections between themselves, other users and objects. On...
Artus Krohn-Grimberghe, Lucas Drumond, Christoph F...
SIGIR
2011
ACM
12 years 7 months ago
Fast context-aware recommendations with factorization machines
The situation in which a choice is made is an important information for recommender systems. Context-aware recommenders take this information into account to make predictions. So ...
Steffen Rendle, Zeno Gantner, Christoph Freudentha...
CIKM
2004
Springer
13 years 8 months ago
Taxonomy-driven computation of product recommendations
Recommender systems have been subject to an enormous rise in popularity and research interest over the last ten years. At the same time, very large taxonomies for product classifi...
Cai-Nicolas Ziegler, Georg Lausen, Lars Schmidt-Th...