Publications | HCAI MMS Group


Journals

EuroReg screenshot

Tommaso Di Noia, Nava Tintarev, Panagiota Fatourou, Markus Schedl
Recommender Systems under European AI Regulations
Communications of the ACM, 2022

MusicAnxietyAcoustic screenshot

Emilia Parada-Cabaleiro, Anton Batliner, Markus Schedl
An Exploratory Study on the Acoustic Musical Properties to Decrease Self-Perceived Anxiety
International Journal of Environmental Research and Public Health, 2022

ExpMusic screenshot

Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam
Explainability in music recommender systems
AI Magazine, 2022

AffectMult screenshot

Mihai Gabriel Constantin, Liviu-Daniel Ştefan, Bogdan Ionescu, Claire-Hélène Demarty, Mats Sjöberg, Markus Schedl, Guillaume Gravier
Affect in Multimedia: Benchmarking Violent Scenes Detection
IEEE Transactions on Affective Computing, 2022

SupportUnderground screenshot

Dominik Kowald, Peter Muellner, Eva Zangerle, Christine Bauer, Markus Schedl, Elisabeth Lex
Support the underground: characteristics of beyond-mainstream music listeners
EPJ Data Science, 2021

PsychInformed screenshot

Elisabeth Lex, Dominik Kowald, Paul Seitlinger, Thi Ngoc Trang Tran, Alexander Felfernig, Markus Schedl
Psychology-Informed Recommender Systems
Foundations and Trends in Information Retrieval, 2021

ListenerModeling screenshot

Markus Schedl, Christine Bauer, Wolfgang Reisinger, Dominik Kowald, Elisabeth Lex
Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes
Frontiers in Artificial Intelligence, 2021

UserModels screenshot

Eva Zangerle, Martin Pichl, Markus Schedl
User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues
Transactions of the International Society for Music Information Retrieval, 2020

RSLeveraging screenshot

Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi
Recommender Systems Leveraging Multimedia Content
ACM Computing Surveys, 2020

ModelingPopularity screenshot

Elisabeth Lex, Dominik Kowald, Markus Schedl
Modeling Popularity and Temporal Drift of Music Genre Preferences
Transactions of the International Society for Music Information Retrieval, 2020

ModelingPeresonalized screenshot

Marko Tkalčič, Markus Schedl, Peter Knees
Preface to the Special Issue on User Modeling for Personalized Interaction with Music
User Modeling and User-Adapted Interaction, 2020

IntUserInterfaces screenshot

Peter Knees, Markus Schedl, Masataka Goto
Intelligent User Interfaces for Music Discovery
Transactions of the International Society for Music Information Retrieval, 2020


Conference and Workshop Proceedings

Tutorial_WSDM_2023 screenshot

Markus Schedl, Emilia Gómez, Elisabeth Lex
Trustworthy Algorithmic Ranking Systems
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), 2023

Demo_WSDM_2023 screenshot

Veronika Arefieva, Roman Egger, Michael Schrefl, Markus Schedl
Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb Experiences
Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), 2023

UnlearningAdversarial screenshot

Christian Ganhör, David Penz, Navid Rekab-saz, Oleg Lesota, Markus Schedl
Unlearning Protected User Attributes in Recommendations with Adversarial Training
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022

EMOMTB screenshot

Alessandro B. Melchiorre, David Penz, Christian Ganhör, Oleg Lesota, Vasco Bezold Rosner Fragoso, Florian Friztl, Emilia Parada-Cabaleiro, Franz Schubert, Markus Schedl
EmoMTB: Emotion-aware Music Tower Blocks
Proceedings of the 2022 ACM International Conference on Multimedia Retrieval (ICMR), 2022

TextureRecognition screenshot

Emilia Parada-Cabaleiro, Maximilian Schmitt, Anton Batliner, Björn Schuller, Markus Schedl
Automatic Recognition of Texture in Renaissance Music
International Society for Music Information Retrieval, 2021

PopBiasGender screenshot

Oleg Lesota, Alessandro B. Melchiorre, Navid Rekab-saz, Stefan Brandl, Dominik Kowald, Elisabeth Lex, Markus Schedl
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Proceedings of the 15th ACM Conference on Recommender Systems (RecSys), 2021

LEMONS screenshot

Alessandro B. Melchiorre, Verena Haunschmid, Markus Schedl, Gerhard Widmer
LEMONS: Listenable Explanations for Music recOmmeNder Systems
Proceedings of the 43rd European Conference on Information Retrieval (ECIR), 2021

DeepGenIR screenshot

Oleg Lesota, Navid Rekab-saz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, Markus Schedl
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models
Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval, 2021

PersonalityCorrelates screenshot

Alessandro B. Melchiorre, Markus Schedl
Personality Correlates of Music Audio Preferences for Modelling Music Listeners
Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization (UMAP), 2020

PersonalityBias screenshot

Alessandro B. Melchiorre, Eva Zangerle, Markus Schedl
Personality Bias of Music Recommendation Algorithms
Proceedings of the 14th ACM Conference on Recommender Systems (RecSys), 2020


Books and Book Chapters

Markus Schedl, Peter Knees, Brian McFee, Dmitry Bogdanov
Editors: Francesco Ricci, Lior Rokach, Bracha Shapira
Chapter: Music Recommendation Systems: Techniques, Use Cases, and Challenges
Recommender Systems Handbook (3rd edition)
Springer, 2022.

Yashar Deldjoo, Markus Schedl, Balazs Hidasi, Yinwei Wei, Xiangnan He
Editors: Francesco Ricci, Lior Rokach, Bracha Shapira
Chapter: Multimedia Recommender Systems: Algorithms and Challenges
Recommender Systems Handbook (3rd edition)
Springer, 2022.


Theses

Katrin Leberfinger
Gender Bias in Content-Based Music Recommendation Systems
Johannes Kepler University Linz, Master's Thesis, 2022