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SIGIR
2010
ACM
15 years 1 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...
BCSHCI
2007
14 years 11 months ago
"The devil you know knows best": how online recommendations can benefit from social networking
The defining characteristic of the Internet today is an abundance of information and choice. Recommender Systems (RS), designed to alleviate this problem, have so far not been ver...
Philip Bonhard, Martina Angela Sasse, Clare Harrie...
ESWA
2002
134views more  ESWA 2002»
14 years 9 months ago
A personalized recommender system based on web usage mining and decision tree induction
A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been...
Yoon Ho Cho, Jae Kyeong Kim, Soung Hie Kim
EUSFLAT
2003
103views Fuzzy Logic» more  EUSFLAT 2003»
14 years 11 months ago
Instance-based collaborative filtering with fuzzy labels
In recommender systems, user ratings of items are often represented in terms of linguistic labels such as “fair” or “very good”. We investigate the potential of fuzzy sets...
Eyke Hüllermeier
UAI
2003
14 years 11 months ago
Collaborative Ensemble Learning: Combining Collaborative and Content-Based Information Filtering via Hierarchical Bayes
Collaborative filtering (CF) and contentbased filtering (CBF) have widely been used in information filtering applications, both approaches having their individual strengths and...
Kai Yu, Anton Schwaighofer, Volker Tresp, Wei-Ying...