Paper Info
Title
Comparative evaluation of recommender system quality
Abstract
Several researchers suggest that the Recommendation Systems (RSs) that are the "best" according to statistical metrics might not be the most satisfactory for the user. We explored this issue through an empirical study that involved 210 users and considered 7 RSs using different recommender algorithms on the same dataset. We measured user's perceived quality of each RS, and compared these results against measures of statistical quality of the considered algorithms as they have been assessed by past studies in the field, highlighting some interesting results.
Year
DOI
Venue
2011
10.1145/1979742.1979896
CHI Extended Abstracts
Keywords
Field
DocType
past study,recommender system quality,recommendation systems,statistical quality,different recommender algorithm,comparative evaluation,empirical study,statistical metrics,interesting result,recommender system,recommender systems
Recommender system,Information retrieval,Computer science,RSS,Empirical research
Conference
Citations 
PageRank 
References 
24
0.90
9
Authors
5
Name
Order
Citations
PageRank
Paolo Cremonesi1130687.23
Franca Garzotto21245203.98
Sara Negro3622.01
Alessandro Papadopoulos428127.10
Roberto Turrin585934.94