%0 Conference Paper %1 Ge_2010 %A Ge, Mouzhi %A Delgado-Battenfeld, Carla %A Jannach, Dietmar %B Proceedings of the fourth ACM conference on Recommender systems - RecSys \textquotesingle10 %D 2010 %I ACM Press %K evaluation recommender recsys2010 serendipity %P 257-260 %R 10.1145/1864708.1864761 %T Beyond accuracy: evaluating recommender systems by coverage and serendipity %U https://doi.org/10.1145%2F1864708.1864761 %X 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 is a variety of other metrics that should be considered when evaluating a RS. In this paper we focus on two crucial metrics in RS evaluation: coverage and serendipity. Based on a literature review, we first discuss both measurement methods as well as the trade-off between good coverage and serendipity. We then analyze the role of coverage and serendipity as indicators of recommendation quality, present novel ways of how they can be measured and discuss how to interpret the obtained measurements. Overall, we argue that our new ways of measuring these concepts reflect the quality impression perceived by the user in a better way than previous metrics thus leading to enhanced user satisfaction.

@inproceedings{Ge_2010, abstract = {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 is a variety of other metrics that should be considered when evaluating a RS. In this paper we focus on two crucial metrics in RS evaluation: coverage and serendipity. Based on a literature review, we first discuss both measurement methods as well as the trade-off between good coverage and serendipity. We then analyze the role of coverage and serendipity as indicators of recommendation quality, present novel ways of how they can be measured and discuss how to interpret the obtained measurements. Overall, we argue that our new ways of measuring these concepts reflect the quality impression perceived by the user in a better way than previous metrics thus leading to enhanced user satisfaction. }, added-at = {2020-11-28T17:50:12.000+0100}, author = {Ge, Mouzhi and Delgado-Battenfeld, Carla and Jannach, Dietmar}, biburl = {https://www.bibsonomy.org/bibtex/20fee49c9770a12467ceecfe39e9f318f/brusilovsky}, booktitle = {Proceedings of the fourth {ACM} conference on Recommender systems - {RecSys} {\textquotesingle}10}, description = {Beyond accuracy | Proceedings of the fourth ACM conference on Recommender systems}, doi = {10.1145/1864708.1864761}, interhash = {a1ce4cff3e9855ea34ffa41521073d91}, intrahash = {0fee49c9770a12467ceecfe39e9f318f}, keywords = {evaluation recommender recsys2010 serendipity}, pages = {257-260}, publisher = {{ACM} Press}, timestamp = {2020-11-28T17:50:46.000+0100}, title = {Beyond accuracy: evaluating recommender systems by coverage and serendipity}, url = {https://doi.org/10.1145%2F1864708.1864761}, year = 2010 }