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» Explaining collaborative filtering recommendations
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WISE
2010
Springer
13 years 5 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
AAAI
2004
13 years 9 months ago
Making Better Recommendations with Online Profiling Agents
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...
Danny Oh, Chew Lim Tan
JMLR
2010
156views more  JMLR 2010»
13 years 2 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...
SIGIR
2002
ACM
13 years 7 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
SDM
2010
SIAM
217views Data Mining» more  SDM 2010»
13 years 6 months ago
Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
Quanquan Gu, Jie Zhou, Chris H. Q. Ding