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ML
2008
ACM
146views Machine Learning» more  ML 2008»
13 years 6 months ago
Improving maximum margin matrix factorization
Abstract. Collaborative filtering is a popular method for personalizing product recommendations. Maximum Margin Matrix Factorization (MMMF) has been proposed as one successful lear...
Markus Weimer, Alexandros Karatzoglou, Alex J. Smo...
CIKM
2010
Springer
13 years 4 months ago
CiteData: a new multi-faceted dataset for evaluating personalized search performance
Personalized search systems have evolved to utilize heterogeneous features including document hyperlinks, category labels in various taxonomies and social tags in addition to free...
Abhay Harpale, Yiming Yang, Siddharth Gopal, Daqin...
GFKL
2007
Springer
180views Data Mining» more  GFKL 2007»
14 years 13 days ago
Content-based Dimensionality Reduction for Recommender Systems
Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommen...
Panagiotis Symeonidis
IMECS
2007
13 years 7 months ago
Investigation for Designing of Context-Aware Recommendation System Using SVM
Abstract Previously, we have proposed two recommendation systems, the Context-aware Information Filtering (C-IF) and Context-aware Collaborative Filtering (C-CF), both of which ar...
Kenta Oku, Shinsuke Nakajima, Jun Miyazaki, Shunsu...
KAIS
2011
102views more  KAIS 2011»
13 years 1 months ago
Symbolic data analysis tools for recommendation systems
Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, throu...
Byron Leite Dantas Bezerra, Francisco de Assis Ten...