Justin Basilico (Netflix), Pablo Castells (Universidad Autónoma de Madrid and Amazon), Paolo Cremonesi (Politecnico di Milano), Maurizio Ferrari Dacrema (Politecnico di Milano)

The Workshop on Learning and Evaluating Recommendations with Impressions (LERI 2023) will focus on all aspects related to leveraging impression data to build and evaluate a recommendation engine. Impressions refer to the items displayed on the screen when a user interacts (or not) with the system and are the product of the whole recommendation engine, as such, impressions constitute a nuanced data source that raises novel research questions, opportunities, and challenges. These may have profound implications for how recommender systems are conceptualized, trained, and evaluated. The goal of LERI 2023 is to both help to coalesce researchers exploring the use of impressions from different perspectives, as well as foster increased interest from the community for this important and underexplored topic. The workshop aims to provide a venue for researchers and practitioners to come together to: (i) share experience and lessons learned; (ii) identify key challenges in the area; (iii) build a common mental model and conceptual framework for thinking and researching on the use of impressions; (iv) identify emerging topics and new opportunities. The workshop also aims to lay bridges between practitioners and academics, encourage a wider availability of impression data sources and leverage industry’s experience to guide and inform academic research.