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Project “Humans and Recommender Systems - Towards a Mutual Understanding” started

The project started with the beginning of September.

Recommender systems (RS) are a central means for supporting users in dealing with information overload (e.g., in online shopping or on streaming platforms). Current RS, however, neglect two important elements when modeling users and RS, leading to a mutual misunderstanding: firstly, RS are not able to capture the actual human decision-making that leads to choosing certain items, and secondly, RS are hardly able to communicate the rationale behind recommendations. In the context of these challenges, the project focuses on music recommendations and strives to enhance the understanding of human decision-making underlying the choice of music in a given situational context. Moreover, the project aims to advance the users' understanding of the decisions that lead to the recommendation of certain (sequences of) tracks.

The project consortium features, besides Eva Zangerle as principal investigator, Markus Schedl (Johannes Kepler University Linz), Peter Knees (Vienna University of Technology), Marcel Zentner (University of Innsbruck, Department of Psychology), and Michael Huber (University of Music and Performing Arts Vienna).

The project is funded by the Austrian Science Fund (FWF), with a budget of 600k Euros and a duration of 36 months.

For more information, please visit the project website at https://humrec.github.io/

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