Article-Journal

Efficient Session-based Recommendation with Contrastive Graph-based Shortest Path Search
Andreas Peintner, Amir Reza Mohammadi, Eva Zangerle
Cite DOI URL
Assessing aesthetic music-evoked emotions in a minute or less: A comparison of the GEMS-45 and the GEMS-9
Peer-Ole Jacobsen, Hannah Strauss, Julia Vigl, Eva Zangerle, Marcel Zentner
Cite DOI
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
PDF Cite DOI URL
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
PDF Cite DOI URL
Content-driven music recommendation: Evolution, state of the art, and challenges
Yashar Deldjoo, Markus Schedl, Peter Knees
Cite DOI URL
Evaluation Perspectives of Recommender Systems: Driving Research and Education (Dagstuhl Seminar 24211)
Christine Bauer, Alan Said, Eva Zangerle
Cite DOI URL
Report on the 3rd Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2023) at RecSys 2023
Evaluation is a central step when developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2023 workshop, held as …
Alan Said, Eva Zangerle, Christine Bauer
PDF Cite DOI URL
Song lyrics have become simpler and more repetitive over the last five decades
Emilia Parada-Cabaleiro, Maximilian Mayerl, Stefan Brandl, Marcin Skowron, Markus Schedl, Elisabeth Lex, Eva Zangerle
Cite DOI
The Emotion-to-Music Mapping Atlas (EMMA): A systematically organized online database of emotionally evocative music excerpts
Hannah Strauss, Julia Vigl, Peer-Ole Jacobsen, Martin Bayer, Francesca Talamini, Wolfgang Vigl, Eva Zangerle, Marcel Zentner
PDF Cite DOI
Differential privacy in collaborative filtering recommender systems: a review
Peter Müllner, Elisabeth Lex, Markus Schedl, Dominik Kowald
PDF Cite DOI URL