Recommender Systems

Beyond Algorithms: Reclaiming the Interdisciplinary Roots of Recommender Systems (BEYOND 2025)

This workshop challenges the machine learning-centric focus of modern recommender systems research by reconnecting the field with its …

Eva Zangerle, Alan Said, Christine Bauer

Beyond Top-1: Addressing Inconsistencies in Evaluating Counterfactual Explanations for Recommender Systems

Explainability in recommender systems (RS) remains a pivotal yet challenging research frontier. Among state-of-the-art techniques, …

Amir Reza Mohammadi, Andreas Peintner, Michael Müller, Eva Zangerle

Hypergraph-based Temporal Modelling of Repeated Intent for Sequential Recommendation

In sequential recommendation scenarios, user intent is a key driver of consumption behavior. However, consumption intents are usually …

Andreas Peintner, Amir Reza Mohammadi, Michael Müller, Eva Zangerle

Reflections on Recommender Systems: Past, Present, and Future (INTROSPECTIVES)

Alan Said, Christine Bauer, Eva Zangerle

Are We Explaining the Same Recommenders? Incorporating Recommender Performance for Evaluating Explainers

Explainability in recommender systems is both crucial and challenging. Among the state-of-the-art explanation strategies, …

Amir Reza Mohammadi, Andreas Peintner, Michael Müller, Eva Zangerle

Exploring the Landscape of Recommender Systems Evaluation: Practices and Perspectives

Recommender systems research and practice are fast-developing topics with growing adoption in a wide variety of information access …

Christine Bauer, Eva Zangerle, Alan Said

Introduction to the Special Issue on Perspectives on Recommender Systems Evaluation

Evaluation plays a vital role in recommender systems—in research and practice—whether for confirming algorithmic concepts or assessing …

Christine Bauer, Alan Said, Eva Zangerle

Second Workshop: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2022)

Eva Zangerle, Christine Bauer, Alan Said