Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction.
M. Ferrari Dacrema, P. Cremonesi, and D. Jannach. Proceedings of the 13th ACM Conference on Recommender Systems, page 101–109. New York, NY, USA, Association for Computing Machinery, (2019)
S. Zhang, and K. Balog. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &$\mathsemicolon$ Data Mining, page 1512-1520. ACM, (August 2020)
N. Hazrati, and F. Ricci. Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, page 95-98. ACM, (July 2022)
J. O'Donovan, and B. Smyth. IUI '05: Proceedings of the 10th international conference on Intelligent user interfaces, page 167--174. New York, NY, USA, ACM Press, (2005)
N. Felicioni, M. Dacrema, and P. Cremonesi. Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, page 10-15. ACM, (June 2021)
Y. Wang, L. Wang, Y. Li, D. He, and T. Liu. Proceedings of the 26th Annual Conference on Learning Theory, volume 30 of Proceedings of Machine Learning Research, page 25--54. Princeton, NJ, USA, PMLR, (June 2013)
G. Schröder, M. Thiele, and W. Lehner. Proceedings of the Workshop on User-Centric Evaluation of Recommender Systems and Their Interfaces, page 78--85. Chicago, USA, CEUR-WS, (October 2011)
M. Dacrema, P. Cremonesi, and D. Jannach. (2019)cite arxiv:1907.06902Comment: Source code available at: https://github.com/MaurizioFD/RecSys2019_DeepLearning_Evaluation.
A. Bellogin, P. Castells, and I. Cantador. Proceedings of the fifth ACM conference on Recommender systems - RecSys 2011, page 333 -- 336. ACM Press, (2011)
M. Ge, C. Delgado-Battenfeld, and D. Jannach. Proceedings of the fourth ACM conference on Recommender systems - RecSys \textquotesingle10, page 257-260. ACM Press, (2010)
J. Schaffer, J. O'Donovan, and T. Höllerer. Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, page 177--185. New York, NY, USA, ACM, (2018)
R. Jäschke, F. Eisterlehner, A. Hotho, and G. Stumme. RecSys '09: Proceedings of the third ACM Conference on Recommender Systems, page 369--372. New York, NY, USA, ACM, (2009)
F. Belém, E. Martins, T. Pontes, J. Almeida, and M. Gonçalves. Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval, page 1033--1042. New York, NY, USA, ACM, (2011)
P. Adamopoulos, and A. Tuzhilin. DiveRS 2011 – ACM RecSys 2011 Workshop on Novelty and Diversity in Recommender Systems, New York, NY, USA, ACM, (October 2011)
J. Fogarty, R. Baker, and S. Hudson. GI '05: Proceedings of Graphics Interface 2005, page 129--136. School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada, Canadian Human-Computer Communications Society, (2005)
J. Fogarty, R. Baker, and S. Hudson. GI '05: Proceedings of Graphics Interface 2005, page 129--136. School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada, Canadian Human-Computer Communications Society, (2005)
R. Jäschke, F. Eisterlehner, A. Hotho, and G. Stumme. RecSys '09: Proceedings of the 2009 ACM Conference on Recommender Systems, New York, NY, USA, ACM, (2009)(to appear).
B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. EC '00: Proceedings of the 2nd ACM conference on Electronic commerce, page 158--167. New York, NY, USA, ACM Press, (2000)
R. Torres, S. Mcnee, M. Abel, J. Konstan, and J. Riedl. International Conference on Digital Libraries,Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries, (2004)