Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Optimizing multiple objectives in collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
Workshop on recommendation utility evaluation: beyond RMSE -- RUE 2012
Proceedings of the sixth ACM conference on Recommender systems
User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm
Proceedings of the 2013 conference on Computer supported cooperative work
How to improve the statistical power of the 10-fold cross validation scheme in recommender systems
Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation
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In this work we describe an approach at multi-objective recommender system evaluation based on a previously introduced 3D benchmarking model. The benchmarking model takes user-centric, business-centric and technical constraints into consideration in order to provide a means of comparison of recommender algorithms in similar scenarios. We present a comparison of three recommendation algorithms deployed in a user study using this 3D model and compare to standard evaluation methods. The proposed approach simplifies benchmarking of recommender systems and allows for simple multi-objective comparisons.