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» Beyond accuracy: evaluating recommender systems by coverage ...
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RECSYS
2010
ACM
13 years 5 months ago
Beyond accuracy: evaluating recommender systems by coverage and serendipity
When we evaluate the quality of recommender systems (RS), most approaches only focus on the predictive accuracy of these systems. Recent works suggest that beyond accuracy there i...
Mouzhi Ge, Carla Delgado-Battenfeld, Dietmar Janna...
WSDM
2012
ACM
246views Data Mining» more  WSDM 2012»
12 years 23 days ago
Auralist: introducing serendipity into music recommendation
Recommendation systems exist to help users discover content in a large body of items. An ideal recommendation system should mimic the actions of a trusted friend or expert, produc...
Yuan Cao Zhang, Diarmuid Ó Séaghdha,...
RECSYS
2010
ACM
13 years 5 months ago
Recommending based on rating frequencies
Since the development of the comparably simple neighborhood-based methods in the 1990s, a plethora of techniques has been developed to improve various aspects of collaborative fil...
Fatih Gedikli, Dietmar Jannach
IAT
2009
IEEE
13 years 12 months ago
Social Trust-Aware Recommendation System: A T-Index Approach
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between us...
Alireza Zarghami, Soude Fazeli, Nima Dokoohaki, Mi...
CSCW
2002
ACM
13 years 5 months ago
On the recommending of citations for research papers
Collaborative filtering has proven to be valuable for recommending items in many different domains. In this paper, we explore the use of collaborative filtering to recommend resea...
Sean M. McNee, Istvan Albert, Dan Cosley, Prateep ...