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JMLR
2010
156views more  JMLR 2010»
8 years 1 months ago
Collaborative Filtering on a Budget
Matrix factorization is a successful technique for building collaborative filtering systems. While it works well on a large range of problems, it is also known for requiring signi...
Alexandros Karatzoglou, Alexander J. Smola, Markus...
DATAMINE
2010
161views more  DATAMINE 2010»
8 years 3 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
WISE
2010
Springer
8 years 4 months ago
Neighborhood-Restricted Mining and Weighted Application of Association Rules for Recommenders
Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Fatih Gedikli, Dietmar Jannach
SP
2002
IEEE
141views Security Privacy» more  SP 2002»
8 years 6 months ago
Collaborative Filtering with Privacy
Server-based collaborative filtering systems have been very successful in e-commerce and in direct recommendation applications. In future, they have many potential applications in...
John F. Canny
SIGIR
2002
ACM
8 years 6 months ago
Collaborative filtering with privacy via factor analysis
Collaborative filtering (CF) is valuable in e-commerce, and for direct recommendations for music, movies, news etc. But today's systems have several disadvantages, including ...
John F. Canny
SIGIR
2008
ACM
8 years 6 months ago
Personalized active learning for collaborative filtering
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Abhay Harpale, Yiming Yang
SIGIR
2008
ACM
8 years 6 months ago
EigenRank: a ranking-oriented approach to collaborative filtering
A recommender system must be able to suggest items that are likely to be preferred by the user. In most systems, the degree of preference is represented by a rating score. Given a...
Nathan Nan Liu, Qiang Yang
ECRA
2007
139views more  ECRA 2007»
8 years 6 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
IR
2006
8 years 6 months ago
A study of mixture models for collaborative filtering
Collaborative filtering is a general technique for exploiting the preference patterns of a group of users to predict the utility of items for a particular user. Three different co...
Rong Jin, Luo Si, Chengxiang Zhai
DEBU
2008
165views more  DEBU 2008»
8 years 6 months ago
A Survey of Attack-Resistant Collaborative Filtering Algorithms
With the increasing popularity of recommender systems in commercial services, the quality of recommendations has increasingly become an important to study, much like the quality o...
Bhaskar Mehta, Thomas Hofmann
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