313 citations · 852 across the 32 of their papers we have counts for
9 papers · 1 filter
My friends also prefer diverse music: homophily and link prediction with user preferences for mainstream, novelty, and diversity in music
Tomislav Duricic, Dominik Kowald, Markus Schedl +1
Homophily describes the phenomenon that similarity breeds connection, i.e., individuals tend to form ties with other people who are similar to themselves in some aspect(s). The sim…
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Oleg Lesota, Alessandro B. Melchiorre, Navid Rekabsaz +4
Several studies have identified discrepancies between the popularity of items in user profiles and the corresponding recommendation lists. Such behavior, which concerns a variety o…
Predicting Music Relistening Behavior Using the ACT-R Framework
Markus Reiter-Haas, Emilia Parada-Cabaleiro, Markus Schedl +3
Providing suitable recommendations is of vital importance to improve the user satisfaction of music recommender systems. Here, users often listen to the same track repeatedly and a…
Content-driven Music Recommendation: Evolution, State of the Art, and Challenges
Yashar Deldjoo, Markus Schedl, Peter Knees
The music domain is among the most important ones for adopting recommender systems technology. In contrast to most other recommendation domains, which predominantly rely on collabo…
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Oleg Lesota, Navid Rekabsaz, Daniel Cohen +3
Existing neural ranking models follow the text matching paradigm, where document-to-query relevance is estimated through predicting the matching score. Drawing from the rich litera…
Current Challenges and Future Directions in Podcast Information Access
Rosie Jones, Hamed Zamani, Markus Schedl +11
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and c…
Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers
Navid Rekabsaz, Simone Kopeinik, Markus Schedl
Societal biases resonate in the retrieved contents of information retrieval (IR) systems, resulting in reinforcing existing stereotypes. Approaching this issue requires established…
TripClick: The Log Files of a Large Health Web Search Engine
Navid Rekabsaz, Oleg Lesota, Markus Schedl +2
Click logs are valuable resources for a variety of information retrieval (IR) tasks. This includes query understanding/analysis, as well as learning effective IR models particularl…
Support the Underground: Characteristics of Beyond-Mainstream Music Listeners
Dominik Kowald, Peter Muellner, Eva Zangerle +3
Music recommender systems have become an integral part of music streaming services such as Spotify and Last.fm to assist users navigating the extensive music collections offered by…