110 citations · 226 across the 8 of their papers we have counts for
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cs.IR2023★ 1 cited
E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender Systems
Patrick John Chia, Giuseppe Attanasio, Jacopo Tagliabue +5
Recommender Systems today are still mostly evaluated in terms of accuracy, with other aspects beyond the immediate relevance of recommendations, such as diversity, long-term user r…
cs.IR2023
EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments
Federico Bianchi, Patrick John Chia, Ciro Greco +5
EvalRS aims to bring together practitioners from industry and academia to foster a debate on rounded evaluation of recommender systems, with a focus on real-world impact across a m…