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UM
2007
Springer
14 years 1 months ago
Feature-Weighted User Model 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 re...
Panagiotis Symeonidis, Alexandros Nanopoulos, Yann...
WEBI
2005
Springer
14 years 1 months ago
Privacy-Preserving Top-N Recommendation on Horizontally Partitioned Data
Collaborative filtering techniques are widely used by many E-commerce sites for recommendation purposes. Such techniques help customers by suggesting products to purchase using o...
Huseyin Polat, Wenliang Du
SIGIR
2010
ACM
13 years 11 months ago
Temporal diversity in recommender systems
Collaborative Filtering (CF) algorithms, used to build webbased recommender systems, are often evaluated in terms of how accurately they predict user ratings. However, current eva...
Neal Lathia, Stephen Hailes, Licia Capra, Xavier A...
SIGKDD
2008
138views more  SIGKDD 2008»
13 years 7 months ago
Learning preferences of new users in recommender systems: an information theoretic approach
Recommender systems are a nice tool to help nd items of interest from an overwhelming number of available items. Collaborative Filtering (CF), the best known technology for recomme...
Al Mamunur Rashid, George Karypis, John Riedl
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