Sciweavers

108 search results - page 1 / 22
» Item Similarity Learning Methods for Collaborative Filtering...
Sort
View
AAAI
2006
13 years 10 months ago
Mixed Collaborative and Content-Based Filtering with User-Contributed Semantic Features
We describe a recommender system which uses a unique combination of content-based and collaborative methods to suggest items of interest to users, and also to learn and exploit it...
Matthew Garden, Gregory Dudek
AH
2008
Springer
14 years 3 months ago
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Abstract. User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a ...
Linas Baltrunas, Francesco Ricci
ECRA
2007
139views more  ECRA 2007»
13 years 9 months ago
Common structure and properties of filtering systems
Recommendation systems have been studied actively since the 1990s. Generally, recommendation systems choose one or more candidates from a set of candidates through a filtering pro...
Junichi Iijima, Sho Ho
ICML
2004
IEEE
14 years 10 months ago
Unifying collaborative and content-based filtering
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
Justin Basilico, Thomas Hofmann
ICDE
2011
IEEE
225views Database» more  ICDE 2011»
13 years 1 months ago
Methods for boosting recommender systems
—Online shopping has grown rapidly over the past few years. Besides the convenience of shopping directly from ones home, an important advantage of e-commerce is the great variety...
Rubi Boim, Tova Milo