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» Explaining collaborative filtering recommendations
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IIR
2010
13 years 6 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
RECSYS
2010
ACM
13 years 5 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
IUI
2009
ACM
14 years 1 months ago
Tagsplanations: explaining recommendations using tags
While recommender systems tell users what items they might like, explanations of recommendations reveal why they might like them. Explanations provide many benefits, from improvi...
Jesse Vig, Shilad Sen, John Riedl
JCDL
2005
ACM
95views Education» more  JCDL 2005»
13 years 10 months ago
Link prediction approach to collaborative filtering
Recommender systems can provide valuable services in a digital library environment, as demonstrated by its commercial success in book, movie, and music industries. One of the most...
Zan Huang, Xin Li, Hsinchun Chen
ECRA
2007
139views more  ECRA 2007»
13 years 4 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