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» Putting Users in Control of their Recommendations
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IEEEARES
2008
IEEE
15 years 4 months ago
Experimental Demonstration of a Hybrid Privacy-Preserving Recommender System
Recommender systems enable merchants to assist customers in finding products that best satisfy their needs. Unfortunately, current recommender systems suffer from various privacy...
Esma Aïmeur, Gilles Brassard, José Man...
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RECSYS
2009
ACM
15 years 4 months ago
Using a trust network to improve top-N recommendation
Top-N item recommendation is one of the important tasks of recommenders. Collaborative filtering is the most popular approach to building recommender systems which can predict ra...
Mohsen Jamali, Martin Ester
RECSYS
2009
ACM
15 years 4 months ago
FeedbackTrust: using feedback effects in trust-based recommendation systems
With the advent of online social networks, the trust-based approach to recommendation has emerged which exploits the trust network among users and makes recommendations based on t...
Samaneh Moghaddam, Mohsen Jamali, Martin Ester, Ja...
ICWSM
2008
14 years 11 months ago
Recommendation of Multimedia Items by Link Analysis and Collaborative Filtering
We investigate two recommendation approaches suitable for online multimedia sharing services. Our first approach, UserRank, recommends items by global interestingness irrespective...
Davin Wong, Ella Bingham, Saara Hyvönen
RECSYS
2010
ACM
14 years 10 months ago
Eye-tracking product recommenders' usage
Recommender systems have emerged as an effective decision tool to help users more easily and quickly find products that they prefer, especially in e-commerce environments. However...
Sylvain Castagnos, Nicolas Jones, Pearl Pu