Report on the 1st Workshop on Measuring the Quality of Explanations in Recommender Systems (QUARE 2022) at SIGIR 2022

Explainable recommenders are systems that explain why an item is recommended, in addition to suggesting relevant items to the users of the system. Although explanations are known to be able to significantly affect a user's decision-making process, significant gaps remain concerning methodologies to evaluate them. This hinders cross-comparison between explainable recommendation approaches and is one of the issues hampering the widespread adoption of explanations in industry settings. The goal of QUARE '22 was to promote discussion upon future research and practice directions around evaluation methodologies for explanations in recommender systems. To that end, we brought together researchers and practitioners from academia and industry in a half-day event, co-located with SIGIR 2022. The workshop's program included two keynote talks, three sessions of technical paper presentations in the form of lightning talks followed by panel discussions, and a final plenary discussion session. Although the area of explanations for recommender systems is still in its early stages, QUARE saw the participation of researchers and practitioners from several fields, laying the groundwork for the creation of a community around this topic and indicating promising directions for future research and development. Date: 15 July, 2022. Website: https://sites.google.com/view/quare-2022/home.