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» Context-Dependent Recommendations with Items Splitting
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IIR
2010
13 years 6 months ago
Context-Dependent Recommendations with Items Splitting
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
Linas Baltrunas, Francesco Ricci
RECSYS
2009
ACM
13 years 11 months ago
Context-based splitting of item ratings in collaborative filtering
Collaborative Filtering (CF) recommendations are computed by leveraging a historical data set of users’ ratings for items. It assumes that the users’ previously recorded ratin...
Linas Baltrunas, Francesco Ricci
WEBI
2005
Springer
13 years 10 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
SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
11 years 7 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
ODR
2008
13 years 6 months ago
A Multi-Agent Architecture for Online Dispute Resolution Services
: Argumentation theory is often used in multi agent-systems to facilitate autonomous agent reasoning and multi-agent interaction. The technology can also be used to develop online ...
Brooke Abrahams, John Zeleznikow