Journals (peer-reviewed)
[J54] Schedl, M., Deldjoo, Y., Castells, P., Yilmaz, E. Introduction to the Special Issue on Trustworthy Recommender Systems, ACM Transactions on Recommender Systems, 2024.

[J53] Adelberger, P., Lesota, O., Eckelt, K., Schedl, M., Streit, M. Iguanodon: A Code-Breaking Game for Improving Visualization Construction Literacy, IEEE Transactions on Visualization and Computer Graphics, 2024.

[J52] Parada-Cabaleiro, E., Mayerl, M., Brandl, S., Skowron, M., Schedl, M., Lex, E., Zangerle, E. Song Lyrics Have Become Simpler and More Repetitive over the Last Five Decades, Nature Scientific Reports, volume 14, number 5531, 2024. Highlight

[J51] Deldjoo, Y., Schedl, M., Knees, P. Content-driven Music Recommendation: Evolution, State of the Art, and Challenges, Computer Science Review, volume 51, 2024. Highlight

[J50] Parada-Cabaleiro, E., Batliner, A., Zentner, M., Schedl, M. Exploring Emotions in Bach Chorales: A Multi-modal Perceptual and Data-driven Study, Royal Society Open Science, volume 10, issue 12, 2023. Highlight

[J49] Müllner, P., Lex, E., Schedl, M., Kowald D. Differential Privacy in Collaborative Filtering Recommender Systems: A Review, volume 6, Frontiers in Big Data - Recommender Systems, 2023.

[J48] Kumar, D., Grosz, T., Rekabsaz, N., Greif, E., Schedl, M. Fairness of Recommender Systems in the Recruitment Domain: An Analysis from Technical and Legal Perspectives, volume 6, Frontiers in Big Data - Recommender Systems, 2023.

[J47] Müllner, P., Lex, E., Schedl, M., Kowald, D. ReuseKNN: Neighborhood Reuse for Differentially-Private KNN-Based Recommendations, ACM Transactions on Intelligent Systems and Technology, volume 14, number 5, pages 80:1-80:29, 2023. Highlight

[J46] Frohmann, M., Karner, M., Khudoyan, S., Wagner, R., Schedl, M. Predicting the Price of Bitcoin Using Sentiment-Enriched Time Series Forecasting, Big Data and Cognitive Computing, 2023.

[J45] Di Noia, T., Ko, I.-Y., Schedl, M. Introduction to the ICWE 2022 Special Issue, Journal of Web Engineering, volume 22, issue 1,  pp. v-viii, 2023.

[J44] Parada-Cabaleiro, E., Batliner, A., Schmitt, M., Schedl, M., Costantini, G., Schuller, B. Perception and Classification of Emotions in Nonsense Speech: Humans Versus Machines, PLOS ONE, volume 18, issue 1, pp. 1-26, 2023.

[J43] Melchiorre, A., Penz, D., Ganhör, C., Lesota, O., Fragoso, V., Friztl, F., Parada-Cabaleiro, E., Schubert, F., Schedl, M. Emotion-aware Music Tower Blocks (EmoMTB): An Intelligent Audiovisual Interface for Music Discovery and Recommendation, International Journal of Multimedia Information Retrieval, volume 12, issue 13, 2023.

[J42] Afchar, D., Melchiorre, A., Schedl, M., Hennequin, R., Epure, E., Moussallam, M. Explainability in Music Recommender Systems, AI Magazine, volume 43, issue 2, pp. 190-208, 2022. Highlight

[J41] Constantin, M.G., Ştefan, L.-D., Ionescu, B., Demarty, C.-H., Sjöberg, M., Schedl, M., Gravier, G. Affect in Multimedia: Benchmarking Violent Scenes Detection, IEEE Transactions on Affective Computing, volume 13, number 1, pp. 347-366, 2022.

[J40] Di Noia, T., Tintarev, N., Fatourou, P., Schedl, M. Recommender Systems Under European AI Regulations, Communications of the ACM, volume 65, issue 4, pp. 69-73, 2022. Highlight

[J39] Parada-Cabaleiro, E., Batliner, A., Schedl, M. An Exploratory Study on the Acoustic Musical Properties to Decrease Self-perceived Anxiety, International Journal of Environmental Research and Public Health, volume 19, number 2, 2022.

[J38] Melchiorre, A., Rekabsaz, N., Parada-Cabaleiro, E., Brandl, S., Lesota, O., Schedl, M. Investigating Gender Fairness of Recommendation Algorithms in the Music Domain, Information Processing & Management, volume 58, number 5, 2021. Highlight

[J37] Lex, E., Kowald, D., Seitlinger, P., Tran, T.N.T., Felfernig, A., Schedl, M. Psychology-informed Recommender Systems, Foundations and Trends in Information Retrieval, volume 15, issue 2, pp. 134-242, 2021. Highlight

[J36] Kowald D., Muellner, P., Zangerle, E., Bauer, C., Schedl, M., Lex, E. Support the Underground: Characteristics of Beyond-Mainstream Music Listeners, EPJ Data Science, volume 10, number 14, 2021. Highlight

[J35] Schedl, M., Bauer, C., Reisinger, W., Kowald, D., Lex, E. Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes, Frontiers in Artificial Intelligence - Machine Learning and Artificial Intelligence, volume 3, 2021.

[J34] Knees, P., Schedl, M., Masataka, G. Intelligent User Interfaces for Music Discovery, Transactions of the International Society of Music Information Retrieval, volume 3, issue 1, pp. 165-179, 2020.

[J33] Deldjoo, Y., Schedl, M., Cremonesi, P., Pasi, G. Recommender Systems Leveraging Multimedia Content, ACM Computing Surveys, volume 53, number 5, pp. 106:1-106:38, 2020. Highlight

[J32] Tkalčič, M., Schedl, M., Knees, P. Preface to the Special Issue on User Modeling for Personalized Interaction with Music, User Modeling and User-Adapted Interaction (UMUAI) - The Journal of Personalization Research, volume 30, number 2, pp. 195-198, 2020.

[J31] Lex, E., Kowald, D., Schedl, M. Modeling Popularity and Temporal Drift of Music Genre Preferences, Transactions of the International Society of Music Information Retrieval, volume 3, issue 1, pp. 17-30, 2020.

[J30] Zangerle, E., Pichl, M., Schedl, M. User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues, Transactions of the International Society of Music Information Retrieval, volume 3, issue 1, pp. 1-16, 2020.

[J29] Schedl, M. Deep Learning in Music Recommendation Systems, Frontiers in Applied Mathematics and Statistics - Mathematics of Computation and Data Science, volume 5, number 44, 2019.

[J28] Zamani, H., Schedl, M., Lamere, P., Chen, C.-W. An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation, ACM Transactions on Intelligent Systems and Technology, volume 10, issue 5, pp. 57:1-57:21, 2019.

[J27] Bauer, C. and Schedl, M. Global and Country-specific Mainstreaminess Measures: Definitions, Analysis, and Usage for Improving Personalized Music Recommendation Systems, PLOS ONE, volume 14, number 6, pp. 1-36, 2019. Highlight

[J26] Vall, A., Quadrana, M., Schedl, M., Widmer, G. Order, Context and Popularity Bias in Next-song Recommendations, International Journal of Multimedia Information Retrieval, volume 8, issue 2, pp. 101-113, 2019.

[J25] Ferwerda. B., Yang, E., Schedl, M., Tkalčič, M. Personality and Taxonomy Preferences, and the Influence of Category Choice on the User Experience for Music Streaming Services, Multimedia Tools and Applications, volume 78, issue 14, pp. 20157-20190, 2019.

[J24] Deldjoo, Y., Dacrema, M.F., Constantin, M.G., Eghbal-zadeh, H., Cereda, S., Schedl, M., Ionescu, B., Cremonesi, P. Movie Genome: Alleviating New Item Cold Start in Movie Recommendation, User Modeling and User-Adapted Interaction (UMUAI) - The Journal of Personalization Research, volume 29, number 2, pp. 291-343, 2019. Highlight

[J23] Vall, A., Dorfer, M., Eghbal-zadeh, H., Schedl, M., Burjorjee, K., Widmer, G. Feature-Combination Hybrid Recommender Systems for Automated Music Playlist Continuation, User Modeling and User-Adapted Interaction (UMUAI) - The Journal of Personalization Research, volume 29, number 2, pp. 527-572, 2019.

[J22] Liu, M., Hu, X., Schedl, M. The Relation of Culture, Socio-economics, and Friendship to Music Preferences: A Large-scale, Cross-country Study, PLOS ONE, volume 13, number 12, pp. 1-29, 2018. Highlight

[J21] Krismayer, T., Schedl, M., Knees, P., Rabiser, R. Predicting User Demographics from Music Listening Information, Multimedia Tools and Applications, 2018.

[J20] Schedl, M., Zamani H., Chen, C.-W., Deldjoo, Y., Elahi, M. Current Challenges and Visions in Music Recommender Systems Research, International Journal of Multimedia Information Retrieval, volume 7, issue 2, 2018.

[J19] Schedl, M. and Bauer, C. An Analysis of Global and Regional Mainstreaminess for Personalized Music Recommender Systems, Journal of Mobile Multimedia, 2018.

[J18] Schedl, M., Gómez, E., Trent, E.S., Tkalčič, M., Eghbal-Zadeh, H., Martorell, A. On the Interrelation between Listener Characteristics and the Perception of Emotions in Classical Orchestra Music, IEEE Transactions on Affective Computing, volume 9, issue 4, pp. 507-525, 2018. Highlight

[J17] Schedl, M. Investigating Country-specific Music Preferences and Music Recommendation Algorithms with the LFM-1b Dataset, International Journal of Multimedia Information Retrieval, volume 6, issue 1, 2017. Highlight

[J16] Schedl, M., Yang, Y.-H., Herrera, P. Introduction to Intelligent Music Systems and Applications, ACM Transactions on Intelligent Systems and Technology, volume 8, issue 2, October 2016.

[J15] Schedl, M., Gómez, E., Urbano, J. Music Information Retrieval: Recent Developments and Applications, Foundations and Trends in Information Retrieval, volume 8, number 2-3, pp. 127-261, 2014. Highlight

[J14] Knees, P. and Schedl, M. A Survey of Music Similarity and Recommendation from Music Context Data, ACM Transactions on Multimedia Computing, Communications and Applications, volume 10, issue 1, 2014.

[J13] Schedl, M., Flexer, A., Urbano, J. The Neglected User in Music Information Retrieval Research, Journal of Intelligent Information Systems, volume 41, issue 3, pp. 523-539, December 2013.

[J12] Urbano, J., Schedl, M., Serra, X. Evaluation in Music Information Retrieval, Journal of Intelligent Information Systems, volume 41, issue 3, pp. 345-369, December 2013.

[J11] Schedl, M., Hauger, D., Urbano J. Harvesting Microblogs for Contextual Music Similarity Estimation - A Co-occurrence-based Framework, Multimedia Systems, May 2013.

[J10] Knees, P., Schedl, M., Celma, Ò. Hybrid Music Information Retrieval: Preface to the Special Issue, International Journal of Multimedia Information Retrieval: Special Issue on Hybrid Music Information Retrieval, volume 2, issue 1, pp. 1-2, March 2013.

[J9] Urbano, J. and Schedl, M. Minimal Test Collections for Low-Cost Evaluation of Audio Music Similarity and Retrieval Systems, International Journal of Multimedia Information Retrieval: Special Issue on Hybrid Music Information Retrieval, volume 2, issue 1, pp. 59-70, January 2013.

[J8] Schnitzer, D., Flexer, A., Schedl, M., Widmer, G. Local and Global Scaling Reduce Hubs in Space, Journal of Machine Learning Research, volume 13, October 2012. Highlight

[J7] Schedl, M. #nowplaying Madonna: A Large-Scale Evaluation on Estimating Similarities Between Music Artists and Between Movies from Microblogs, Information Retrieval, volume 15, issue 3-4, pp. 183-217, June 2012.

[J6] Schedl, M., Pohle, T., Knees, P., Widmer, G. Exploring the Music Similarity Space on the Web, ACM Transactions on Information Systems, volume 29, number 3, article 14, July 2011. Highlight

[J5] Schedl, M., Widmer, G., Knees, P., Pohle, T. A Music Information System Automatically Generated via Web Content Mining Techniques, Information Processing & Management, volume 47, pp. 426-439, 2011.

[J4] Schedl, M. and Pohle, T. Enlightening the Sun: A User Interface to Explore Music Artists via Multimedia Content, Multimedia Tools and Applications: Special Issue on Semantic and Digital Media Technologies, volume 49, number 1, August 2010.

[J3] Knees, P., Schedl, M., Pohle, T., Widmer, G. Exploring Music Collections in Virtual Landscapes, IEEE MultiMedia, volume 14, number 3, pp. 46-54, July-September 2007.

[J2] Pohle, T., Knees, P., Schedl, M., Pampalk, E., Widmer G. "Reinventing The Wheel": A Novel Approach to Music Player Interface, IEEE Transactions on Multimedia, volume 9, issue 3, pp. 567-575, 2007.

[J1] Schedl, M., Pampalk, E., Widmer, G. Intelligent Structuring and Exploration of Digital Music Collections, e&i - Elektrotechnik und Informationstechnik, volume 122, issue 7/8, 2005.
Conference Proceedings (peer-reviewed)
[C245] Masoudian, S., Frohmann, M., Rekabsaz, N., Schedl, M. Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization, Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, USA, November 2024.

[C244] Frohmann, M., Sterner, I., Vulić, I., Minixhofer, B., Schedl, M. Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation, Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, USA, November 2024.

[C243] Saad Saeed, M., Nawaz, S., Moscati, M., Kumar Das, R., Salman Tahir, M., Zaigham Zaheer, M., Irzam Liaqat, M., Haris Khan, M., Nandakumar, K., Haroon Yousaf, M., Schedl, M. A Synopsis of FAME 2024 Challenge: Associating Faces with Voices in Multilingual Environments, Proceedings of the ACM Multimedia 2024, Melbourne, Australia, October-November 2024.

[C242] Schedl, M., Lesota, O., Masoudian, S. The Importance of Cognitive Biases in the Recommendation Ecosystem: Evidence of Feature-Positive Effect, Ikea Effect, and Cultural Homophily, Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS @ RecSys 2024), Bari, Italy, October 2024.

[C241] Ganhör, C., Moscati, M., Nawaz, S., Hausberger, A., Schedl, M. A Multimodal Single-branch Embedding Network for Recommendation in Cold-start and Missing Modality Scenarios, Proceedings of the 18th ACM Conference on Recommender Systems (RecSys 2024), Bari, Italy, October 2024.

[C240] Lesota, O., Geiger, J., Walder, M., Kowald, D., Schedl, M. Oh, Behave! Country Representation Dynamics Created by Feedback Loops in Music Recommender Systems, Proceedings of the 18th ACM Conference on Recommender Systems (RecSys 2024), Bari, Italy, October 2024.

[C239] Escobedo, G, Ganhör, C., Brandl, S., Augstein, M., Schedl, M. Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial Training, Proceedings of the 5th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS @ SIGIR 2024), Washington D.C., USA, July 2024.

[C238] Escobedo, G., Moscati, M., Müllner, P., Kopeinik, S., Kowald, D., Lex, E., Schedl M. Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), Vilnius, Lithuania, September 2024.

[C237] Melchiorre, A. B., Masoudian, S., Kumar, D., Schedl, M. Modular Debiasing of Latent User Representations in Prototype-based Recommender Systems, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024), Vilnius, Lithuania, September 2024.

[C236] Schedl, M., Anelli, V.W., Lex, E. Trustworthy User Modeling and Recommendation From Technical and Regulatory Perspectives, Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2024), Cagliari, Italy, July 2024.

[C235] Moscati, M., Strauß, H., Jacobsen, P.-O., Peintner, A., Zangerle, E., Zentner, M., Schedl, M. Emotion-Based Music Recommendation from Quality Annotations and Large-Scale User-Generated Tags, Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2024), Cagliari, Italy, July 2024.

[C234] Masoudian, S., Volaucnik, C., Schedl, M., Rekabsaz, N. Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters, Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024), Malta, March 2024.

[C233] Ratz, L., Schedl, M., Kopeinik, S., Rekabsaz, N. Measuring Bias in Search Results Through Retrieval List Comparison, Proceedings of the 46th European Conference on Information Retrieval (ECIR 2024), Glasgow, Scotland, March 2024.

[C232] Müllner, P., Lex, E., Schedl, M., Kowald, D. The Impact of Differential Privacy on Recommendation Accuracy and Popularity Bias, Proceedings of the 46th European Conference on Information Retrieval (ECIR 2024), Glasgow, Scotland, March 2024.

[C231] Schedl, M., Moscati, M., Sguerra, B., Hennequin, R., Lex, E. Psychology-informed Information Access Systems Workshop, Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM 2024), Mérida, Mexico, March 2024.

[C230] Stadler, A., Parada-Cabaleiro, E., Schedl, M. Towards Potential Applications of Machine Learning in Computer-Assisted Vocal Training, Proceedings of the 16th International Symposium on Computer Music Multidisciplinary Research (CMMR 2023), Tokyo, Japan, November 2023.

[C229] Parada-Cabaleiro, E., Batliner, A., Schmitt, M., Schuller, B., and Schedl, M. Music Emotions in Solo Piano: Bridging the Gap Between Human Perception and Machine Learning, Proceedings of the 16th International Symposium on Computer Music Multidisciplinary Research (CMMR 2023), Tokyo, Japan, November 2023.

[C228] Kumar, D., Grosz, T., Greif, E., Rekabsaz, N., Schedl, M. Identifying Words in Job Advertisements Responsible for Gender Bias in Candidate Ranking Systems via Counterfactual Learning, Proceedings of the 3rd Workshop on Recommender Systems for Human Resources (RecSys in HR @ RecSys 2023), Singapore, September 2023.

[C227] Moscati, M., Deldjoo, Y., Carparelli, G.D., Schedl, M. Multiobjective Hyperparameter Optimization of Recommender Systems, Proceedings of the 3rd Workshop on Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES @ RecSys 2023), Singapore, September 2023.

[C226] Moscati, M., Wallmann, C., Reiter-Haas, M., Kowald, D., Lex, E., Schedl, M. Integrating the ACT-R Framework with Collaborative Filtering for Explainable Sequential Music Recommendation, Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 2023. Highlight

[C225] Schedl, M., Anelli, V.W., Lex, E. Trustworthy Recommender Systems: Technical, Ethical, Legal, and Regulatory Perspectives, Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 2023.

[C224] Romanov Geleta, R., Eckelt, K., Parada-Cabaleiro, E., Schedl, M. Exploring Intensities of Hate Speech on Social Media: A Case Study on Explaining Multilingual Models with XAI, Proceedings of the 4th Conference on Language, Data and Knowledge (LDK 2023), Vienna, Austria, September 2023.

[C223] Masoudian, S., Koutini, K., Schedl, M., Widmer, M., and Rekabsaz, N. Domain Information Control at Inference Time for Acoustic Scene Classification, Proceedings of the 31st European Signal Processing Conference (EUSIPCO), Helsinki, Finland, September 2023.

[C222] Hauzenberger, L., Masoudian, S., Kumar, D., Schedl, M., and Rekabsaz, N. Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks, Findings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), Toronto, Canada, July 2023.

[C221] Lesota, O., Escobedo, G., Deldjoo, Y., Ferwerda, B., Kopeinik, S., Lex, E., Rekabsaz, N., Schedl, M. Computational Versus Perceived Popularity Miscalibration in Recommender Systems, Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023), Taipei, Taiwan, July 2023. Highlight

[C220] Kumar, D., Lesota, O., Zerveas, G., Cohen, D., Eickhoff, C., Schedl, M., Rekabsaz, N. Parameter-efficient Modularised Bias Mitigation via AdapterFusion, Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), Dubrovnik, Croatia, May 2023.

[C219] Kowald, D., Mayr, G., Schedl, M., Lex, E. A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations, Proceedings of the 4th International Workshop on Algorithmic Bias in Search and Recommendation (BIAS 2023) at the 44th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2023.

[C218] Kopeinik, S., Mara, M., Ratz, L., Krieg K., Schedl, M., and Rekabsaz N. Show me a "Male Nurse"! How Gender Bias is Reflected in the Query Formulation of Search Engine Users, Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI 2023), Hamburg, Germany, April 2023. Highlight

[C217] Ferwerda, B., Ingesson, E., Berndl, M., Schedl, M. I Don’t Care How Popular You Are! Investigating Popularity Bias From a User’s Perspective, Proceedings of the 8th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2023), Austin, USA, March 2023.

[C216] Krieg, K., Parada-Cabaleiro, E., Medicus, G., Lesota, O., Schedl, M., Rekabsaz, N. Grep-BiasIR: A Dataset for Investigating Gender Representation Bias in Information Retrieval Results, Proceedings of the 8th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2023), Austin, USA, March 2023.

[C215] Arefieva, V., Egger, R., Schrefl, M., Schedl, M. 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), Singapore, February-March 2023.

[C214] Schedl, M., Gómez, E., Lex, E. Trustworthy Algorithmic Ranking Systems, Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), Singapore, February-March 2023.

[C213] Lesota, O., Parada-Cabaleiro, E., Brandl, S., Lex, E., Rekabsaz, N., Schedl, M. Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms, Proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR 2022), Bengaluru, India, December 2022. Best Student Paper Award

[C212] Mayerl, M., Brandl, S., Specht, G., Schedl, M., Zangerle, E. Verse Versus Chorus: Structure-aware Feature Extraction for Lyrics-based Genre Recognition, Proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR 2022), Bengaluru, India, December 2022.

[C211] Moscati, M., Parada-Cabaleiro, E., Deldjoo, Y., Zangerle, E., and Schedl, M. Music4All-Onion — A Large-Scale Multi-faceted Content-Centric Music Recommendation Dataset, Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), Atlanta, USA, October 2022.

[C210] Peintner, A., Moscati, M., Parada-Cabaleiro, E., Schedl, M. and Zangerle, E. Unsupervised Graph Embeddings for Session-based Recommendation with Item Features, Proceedings of the 7th Workshop on Context-aware Recommender Systems (CARS @ RecSys 2022), Seattle, USA, September 2022.

[C209] Lesota, O., Brandl, S., Wenzel, M., Melchiorre, A.B., Lex, E., Rekabsaz, N., Schedl, M. Exploring Cross-group Discrepancies in Calibrated Popularity for Accuracy/Fairness Trade-off Optimization, Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems (MORS @ RecSys 2022), Seattle, USA, September 2022.

[C208] Melchiorre, A., Rekabsaz, N., Ganhör, C., Schedl, M. ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations, Proceedings of the 16th ACM Recommender Systems Conference (RecSys 2022), Seattle, USA, September 2022. Highlight

[C207] Lex, E. and Schedl, M. Psychology-informed Recommender Systems Tutorial, Proceedings of the 16th ACM Recommender Systems Conference, Seattle, USA, September 2022.

[C206] Schedl, M., Rekabsaz, N., Lex, E., Grosz, T., Greif, E. Multiperspective and Multidisciplinary Treatment of Fairness in Recommender Systems Research, Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2022), Barcelona, Spain, July 2022.

[C205] Schedl, M., Gómez, E., Lex, E. Retrieval and Recommendation Systems at the Crossroads of Artificial Intelligence, Ethics, and Regulation, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), Madrid, Spain, July 2022.

[C204] Ganhör, C., Penz, D., Rekabsaz, N., Lesota, O., Schedl, M. Unlearning Protected User Attributes in Recommendations with Adversarial Training, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), Madrid, Spain, July 2022. Highlight

[C203] Melchiorre, A., Penz, D., Ganhör, C., Lesota, O., Fragoso, V., Friztl, F., Parada-Cabaleiro, E., Schubert, F., Schedl, M. EmoMTB: Emotion-aware Music Tower Blocks, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2022), Newark, USA, June 2022.

[C202] Tommasini, R., Roy, S.B., Wang, X., Wang, H., Ji, H., Han, J., Nakov, P., Da San Martino, G., Alam, F., Schedl, M., Lex, E., Bharadwaj, A., Cormode, G., Dojchinovski, M., Forberg, J., Frey, J., Bonte, P., Balduini, M., Belcao, M., Della Valle, E., Yu, J., Yin, H., Chen, T., Liu, H., Wang, Y., Fan, W., Liu, X., Dacon, J., Lye, L., Tang, J., Gionis, A., Neumann, S., Ordozgoiti, B., Razniewski, S., Arnaout, H., Ghosh, S., Suchanek, F., Wu, L., Chen, Y., Li, Y., Liu, B., Ilievski, F., Garijo, D., Chalupsky, H., Pedro, P., Kanellos, I., Sacharidis, D., Vergoulis, T., Choudhary, N., Rao, N., Subbian, K., Sengamedu, S., Reddy, C.K., Victor, F., Haslhofer, B., Katsogiannis-Meimarakis, G., Koutrika, G., Jin, S., Koutra, D., Zafarani, R., Tsvetkov, Y., Balachandran, V., Kumar, S., Zhao, X., Chen, B., Guo, H., Wang, Y., Tang, R., Zhang, Y., Wang, W., Wu, P., Feng, F., He, X. Accepted Tutorials at The Web Conference 2022, Companion Proceedings of the Web Conference 2022, Online, April 2022.

[C201] Krieg, K., Parada-Cabaleiro, E., Schedl, M., Rekabsaz, N. Do Perceived Gender Biases in Retrieval Results Affect Users' Relevance Judgements?, Proceedings of the 3rd International Workshop on Algorithmic Bias in Search and Recommendation (BIAS 2022) at the 44th European Conference on Information Retrieval (ECIR 2022), Stavanger, Norway, April, 2022.

[C200] Lex, E. and Schedl, M. Psychology-informed Recommender Systems: A Human-centric Perspective on Recommender Systems, Proceedings of the 7th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2022), Virtual, March 2022.

[C199] Schedl, M., Brandl, S., Lesota, O., Parada-Cabaleiro, E., Penz, D., Rekabsaz, N. LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis, Proceedings of the 7th ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2022), Virtual, March 2022. Highlight

[C198] Duricic, T., Kowald, D., Schedl M., Lex, E. My Friends Also Prefer Diverse Music: Homophily and Link Prediction With User Preferences for Mainstream, Novelty, and Diversity in Music, Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2021), Virtual, November 2021.

[C197] Brandl, S. and Schedl, M. Interactively Exploring Similarities Between Music Genres Based on User-generated Tags, Late-Breaking/Demos of the 22nd International Society for Music Information Retrieval Conference (ISMIR 2021), Virtual, November 2021.

[C196] Schweiger, H., Parada-Cabaleiro, E., Schedl, M. Does Track Sequence in User-generated Playlists Matter?, Proceedings of the 22nd International Society for Music Information Retrieval Conference (ISMIR 2021), Virtual, November 2021.

[C195] Parada-Cabaleiro, E., Schmitt, M., Batliner, A., Schuller, B., and Schedl, M. Automatic Recognition of Texture in Renaissance Music, Proceedings of the 22nd International Society for Music Information Retrieval Conference (ISMIR 2021), Virtual, November 2021.

[C194] Krauck, A., Penz, D., Schedl, M. Team JKU-AIWarriors in the ACM Recommender Systems Challenge 2021: Lightweight XGBoost Recommendation Approach Leveraging User Features, Proceedings of the RecSys Challenge Workshop 2021 at the 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, the Netherlands, October-November 2021.

[C193] Reiter-Haas, M., Parada-Calabeiro, E., Schedl, M., Motamedi, E., Tkalčič, M., Lex, E. Predicting Music Relistening Behavior Using the ACT-R Framework, Proceedings of the 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, the Netherlands, October-November 2021.

[C192] Lesota, O., Melchiorre, A., Rekabsaz, N., Brandl, S., Kowald, D., Lex, E., Schedl, M. Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?, Proceedings of the 15th ACM Conference on Recommender Systems (RecSys 2021), Amsterdam, the Netherlands, October-November 2021.

[C191] Lesota, O., Rekabsaz, N., Cohen, D., Grasserbauer, K., Eickhoff, C. and Schedl, M. A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models, Proceedings of the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR 2021), Online, July 2021.

[C190] Jones, R., Zamani, H., Schedl, M., Chen, C.-W., Reddy, S., Clifton, A., Karlgren, J., Hashemi, H., Pappu, A., Nazari, Z., Yang, L., Semerci, O., Bouchard, H., Carterette B. Current Challenges and Future Directions in Podcast Information Access, Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), Online, July 2021.

[C189] Rekabsaz, N., Kopeinik, S., Schedl, M. Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation of BERT Rankers, Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), Online, July 2021. Highlight

[C188] Rekabsaz, N., Lesota, O., Schedl, M., Brassey, J., and Eickhoff, E. TripClick: The Log Files of a Large Health Web Search Engine, Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), Online, July 2021.

[C187] Stelzmüller, C., Tanzer, S., Schedl, M. Cross-city Analysis of Location-based Sentiment in User-generated Text, Proceedings of the 11th International Workshop on Location and the Web (LocWeb 2021), WWW 2021 Companion, Virtual, April 2021.

[C186] Melchiorre, A., Haunschmid, V., Schedl, M., Widmer, G. LEMONS: Listenable Explanations for Music recOmmeNder Systems, Proceedings of the 43rd European Conference on Information Retrieval (ECIR 2021), Virtual, March-April 2021.

[C185] Liu, M., Zangerle, E., Hu, X., Melchiorre, A., Schedl, M. Pandemics, Music, and Collective Sentiment: Evidence From the Outbreak of COVID-19, Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR 2020), Virtual, October 2020.

[C184] Robinson, K., Brown, D., Schedl, M. User Insights on Diversity in Music Recommendation Lists, Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR 2020), Virtual, October 2020.

[C183] Melchiorre, A., Zangerle, E., Schedl, M. Personality Bias of Music Recommendation Algorithms, Proceedings of the 14th ACM Conference on Recommender Systems (RecSys 2020), Virtual, September 2020. Highlight

[C182] Rekabsaz, N. and Schedl, M. Do Neural Ranking Models Intensify Gender Bias?, Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China, July 2020.

[C181] Schedl, M., Mayr, M., Knees, P. Music Tower Blocks: Multi-Faceted Exploration Interface for Web-Scale Music Access, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2020), Dublin, Ireland, June 2020. Best Demo Award

[C180] Melchiorre, A.B. and Schedl, M. Personality Correlates of Music Audio Preferences for Modelling Music Listeners, Proceedings of the 28th International Conference on User Modeling, Adaptation and Personalization (UMAP 2020), Genoa, Italy, July 2020.

[C179] Kowald, D., Schedl, M., Lex, E. The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study, Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020), Lisbon, Portugal, April 2020.

[C178] Kowald, D., Lex, E., Schedl, M. Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations, Proceedings of the 25th Conference on Intelligent User Interfaces (IUI 2020): Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE 2020), Cagliari, Italy, March 2020.

[C177] Kowald, D., Lex, E., Schedl, M. Modeling Artist Preferences for Personalized Music Recommendations, Late-Breaking/Demos of the 20th International Society for Music Information Retrieval Conference (ISMIR 2019), Delft, the Netherlands, November 2019.

[C176] Knees, P., Schedl, M., Goto, M. Intelligent User Interfaces for Music Discovery: The Past 20 Years and What's to Come, Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR 2019), Delft, the Netherlands, November 2019.

[C175] Bauer, C., Schedl, M., Angerer, V., Wegenkittl, S. Tastalyzer: Audiovisual Exploration of Urban and Rural Variations in Music Taste, Proceedings of the ACM Multimedia 2019, Nice, France, October 2019.

[C174] Costanzo, L.L., Deldjoo, Y., Dacrema, M.F., Schedl, M., and Cremonesi P. Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features, Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2019), Copenhagen, Denmark, September 2019.

[C173] Deldjoo, Y., Schedl, M., Elahi, M. Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content, Proceedings of the 17th International Conference on Content-based Multimedia Indexing (CBMI 2019), Dublin, Ireland, September 2019.

[C172] Deldjoo, Y. and Schedl, M. Retrieving Relevant and Diverse Movie Clips Using the MFVCD-7K Multifaceted Video Clip Dataset, Proceedings of the 17th International Conference on Content-based Multimedia Indexing (CBMI 2019), Dublin, Ireland, September 2019. Best Short Paper Award

[C171] Schedl, M. Genre Differences of Song Lyrics and Artist Wikis: An Analysis of Popularity, Length, Repetitiveness, and Readability, Proceedings of the Web Conference 2019 (WWW 2019), San Francisco, USA, May 2019. Highlight

[C170] Bauer, C. and Schedl, M. Cross-country User Connections in an Online Social Network for Music, ACM CHI '19 Extended Abstracts on Human Factors in Computing Systems (CHI 2019), Glasgow, Scotland, May 2019.

[C169] Knees, P., Schedl, M., Fiebrink, R. Intelligent Music Interfaces for Listening and Creation, Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI ’19 Companion), Los Angeles, USA, March 2019.

[C168] Bauer, C. and Schedl, M. A Cross-Country Investigation of User Connection Patterns in Online Social Networks, Proceedings of the 52nd Hawaii International Conference on System Sciences (HICSS 2019), Maui, Hawaii, USA, January 2019.

[C167] Deldjoo, Y., Constantin, M.G., Dritsas, A., Ionescu, B., and Schedl, M. The MediaEval 2018 Movie Recommendation Task: Recommending Movies Using Content, Working Notes Proceedings of MediaEval 2018: Multimedia Benchmark Workshop, Sophia Antipolis, France, October 2018.

[C166] Hamad, M.M., Skowron, M., Schedl, M. Regressing Controversy of Music Artists from Microblogs, Proceedings of the 30th International Conference on Tools with Artificial Intelligence (ICTAI 2018), Volos, Greece, November 2018.

[C165] Chen, C.-W., Lamere, P., Schedl, M., Zamani, H. RecSys Challenge 2018: Automatic Music Playlist Continuation, Proceedings of the 12th ACM Conference on Recommender Systems (RecSys 2018), Vancouver, Canada, October 2018.

[C164] Deldjoo, Y., Constantin, M.G., Eghbal-zadeh, H., Schedl, M., Ionescu, B., Cremonesi, P. Audio-Visual Encoding of Multimedia Content to Enhance Movie Recommendations, Proceedings of the 12th ACM Conference on Recommender Systems (RecSys 2018), Vancouver, Canada, October 2018.

[C163] Deldjoo, Y., Schedl, M., Hidasi, B., Knees, P. Multimedia Recommender Systems, Proceedings of the 12th ACM Conference on Recommender Systems (RecSys 2018), Vancouver, Canada, October 2018.

[C162] Vall, A., Quadrana, M., Schedl, M., Widmer, G. The Importance of Song Context and Song Order in Automated Music Playlist Generation, Proceedings of the 15th International Conference on Music Perception and Cognition (ICMPC 2018) and 10th Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM 2018), Graz, Austria, July 2018.

[C161] Schedl, M., Knees, P., Gouyon, F. Overview and New Challenges of Music Recommendation Research in 2018, Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR 2018), Paris, France, September 2018.

[C160] Bauer, C., Schedl, M. Investigating Cross-Country Relationship between Users' Social Ties and Music Mainstreaminess, Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR 2018), Paris, France, September 2018.

[C159] Zangerle, E., Pichl, M., Schedl, M. Culture-Aware Music Recommendation, Proceedings of the 26th International Conference on User Modeling, Adaptation and Personalization (UMAP 2018), Singapore, July 2018.

[C158] Deldjoo, Y., Constantin, M.G., Ionescu, B., Schedl, M. MMTF-14K: A Multifaceted Movie Trailer Dataset for Recommendation and Retrieval, Proceedings of the 9th ACM Multimedia Systems Conference (MMSys 2018), Amsterdam, the Netherlands, June 2018.

[C157] Deldjoo, Y., Schedl, M., Cremonesi, P., Pasi, G. Content-Based Multimedia Recommendation Systems: Definition and Application Domains, Proceedings of the 9th Italian Information Retrieval Workshop (IIR 2018), Rome, Italy, May 2018.

[C156] Schedl, M., Wiechert, E., Bauer, C. The Effects of Real-world Events on Music Listening Behavior: An Intervention Time Series Analysis, Proceedings of the Web Conference 2018 (WWW 2018), Lyon, France, April 2018. Highlight

[C155] Knees, P., Schedl, M., Fiebrink, R. IUI’18 Workshop on Intelligent Music Interfaces for Listening and Creation (MILC), Proceedings of the 23rd ACM International Conference on Intelligent User Interfaces (IUI 2018): Workshop on Intelligent Music Interfaces for Listening and Creation (MILC 2018), Tokyo, Japan, March 2018.

[C154] Esswein, C., Schedl, M., Zangerle, E. geMsearch: Personalized Explorative Music Search, Proceedings of the 23rd ACM International Conference on Intelligent User Interfaces (IUI 2018): Workshop on Intelligent Music Interfaces for Listening and Creation (MILC 2018), Tokyo, Japan, March 2018.

[C153] Vall, A., Dorfer, M., Schedl, M., Widmer, G. A Hybrid Approach to Music Playlist Continuation Based on Playlist-Song Membership, Proceedings of the 33rd ACM Symposium on Applied Computing (SAC 2018), Pau, France, April 2018.

[C152] Rudinac, S., Chua, T.S., Diaz-Ferreyra, N., Friedland, G., Gornostaja, T., Huet, B., Kaptein, R., Lindén, K., Moens, M.-F., Peltonen, J., Redi, M., Schedl, M., Shamma, D.A., Smeaton, A., and Xie, L., Rethinking Summarization and Storytelling for Modern Social Multimedia, Proceedings of the 24th International Conference on Multimedia Modeling (MMM 2018), Bangkok, Thailand, February 2018.

[C151] Bauer, C. and Schedl, M. On the Importance of Considering Country-specific Aspects on the Online-Market: An Example of Music Recommendation Considering Country-Specific Mainstream, Proceedings of the 51th Hawaii International Conference on System Sciences (HICSS 2018), Waikoloa Village, Hawaii, USA, January 2018.

[C150] Schedl, M. and Bauer, C. Introducing Global and Regional Mainstreaminess for Improving Personalized Music Recommendation, Proceedings of the 15th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2017), Salzburg, Austria, December 2017. Best Paper Award

[C149] Schedl, M. and Ferwerda, B. Large-scale Analysis of Group-specific Music Genre Taste From Collaborative Tags, Proceedings of the 19th IEEE International Symposium on Multimedia (ISM), Taichung, Taiwan, December 2017.

[C148] Pichl, M., Zangerle, E., Schedl, M. Mining Culture-Specific Music Listening Behavior from Social Media Data, Proceedings of the 19th IEEE International Symposium on Multimedia (ISM), Taichung, Taiwan, December 2017.

[C147] Schedl, M., Lemmerich, F., Ferwerda, B., Skowron, M., and Knees, P. Indicators of Country Similarity in Terms of Music Taste, Cultural, and Socio-economic Factors, Proceedings of the 19th IEEE International Symposium on Multimedia (ISM), Taichung, Taiwan, December 2017.

[C146] Koutini, K., Imenina, A., Dorfer, M., Gruber, A.R., Schedl, M. MediaEval 2017 AcousticBrainz Genre Task: Multilayer Perceptron Approach, Working Notes Proceedings of MediaEval 2017: Multimedia Benchmark Workshop, Dublin, Ireland, September 2017.

[C145] Jetzinger, F., Huemer, F., Schedl, M. Towards Predicting the Popularity of Music Artists, Proceedings of the 10th International Workshop on Machine Learning and Music (MML 2017), Barcelona, Spain, October 2017.

[C144] Liu, M., Hu, X., Schedl, M. Artist Preferences and Cultural, Socio-economic Distances Across Countries: A Big Data Perspective, Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR 2017), Suzhou, China, October 2017.

[C143] Schedl, M., Zamani, H., Chen, C.-W., Deldjoo, Y., Elahi, M. RecSys Challenge 2018: Automatic Playlist Continuation, Late-Breaking/Demos of the 18th International Society for Music Information Retrieval Conference (ISMIR 2017), Suzhou, China, October 2017.

[C142] Pálmason, H., Jónsson, B. Þ., Amsaleg, L., Schedl, M., and Knees, P. On Competitiveness of Nearest-Neighbor Based Music Classification: A Methodological Critique, Proceedings of the 10th International Conference on Similarity Search and Applications (SISAP 2017), Munich, Germany, October 2017.

[C141] Schedl, M. and Bauer, C. Online Music Listening Culture of Kids and Adolescents: Listening Analysis and Music Recommendation Tailored to the Young, Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017): International Workshop on Children and Recommender Systems (KIDREC 2017), Como, Italy, August 2017.

[C140] Vall, A., Eghbal-zadeh, Dorfer, M., Schedl, M. Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features, Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017): Workshop on Deep Learning for Recommender Systems (DLRS 2017), Como, Italy, August 2017.

[C139] Ferwerda, B., Tkalcic, M., Schedl, M. Personality Traits and Music Genre Preferences: How Music Taste Vary Over Age Groups, Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017): Workshop on Temporal Reasoning in Recommender Systems (TempRSS 2017), Como, Italy, August 2017.

[C138] Vall, A., Quadrana, M., Schedl, M., Widmer, G., Cremonesi, P. The Importance of Song Context in Music Playlists, Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August 2017.

[C137] Schedl, M., Knees, P., Gouyon, F. New Paths in Music Recommender Systems Research, Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August 2017.

[C136] Pálmason, H., Jónsson, B. Þ., Schedl, M., Knees, P. Music Genre Classification Revisited: An In-Depth Examination Guided by Music Experts, Proceedings of the 13th International Symposium on Computer Music Multidisciplinary Research (CMMR 2017), Porto, Portugal, September 2017.

[C135] Schedl, M. and Bauer, C. Distance- and Rank-based Music Mainstreaminess Measurement, Proceedings of the 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017): Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2017), Bratislava, Slovakia, July 2017.

[C134] Bauer, C. and Schedl, M. Introducing Surprise and Opposition by Design in Recommender Systems, Proceedings of the 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017): Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2017), Bratislava, Slovakia, July 2017.

[C133] Deldjoo, Y., Cremonesi, P., Schedl, M., Quadrana, M. The Effect of Different Video Summarization Models on the Quality of Video Recommendation Based on Low-level Visual Features, Proceedings of the 15th International Workshop on Content-based Multimedia Indexing (CBMI 2017), Florence, Italy, June 2017.

[C132] Krismayer, T., Schedl, M., Knees, P., Rabiser, R. Prediction of User Demographics from Music Listening Habits, Proceedings of the 15th International Workshop on Content-based Multimedia Indexing (CBMI 2017), Florence, Italy, June 2017. Highlight

[C131] Ferwerda, B., Tkalčič, M., Schedl, M. Personality Traits and Music Genres: What Do People Prefer to Listen To?, Proceedings of the 25th International Conference on User Modeling, Adaptation and Personalization (UMAP 2017), Bratislava, Slovakia, July 2017. Highlight

[C130] Graus, M., Ferwerda, B., Schedl, M., Tkalčič, M., Willemsen, M., Germanakos, P. IUI’17 Companion-Workshop Summary for HUMANIZE’17, Companion of the 22nd ACM International Conference on Intelligent User Interfaces (IUI 2017), Limassol, Cyprus, March 2017.

[C129] Schedl, M. Intelligent User Interfaces for Social Music Discovery and Exploration of Large-scale Music Repositories, Proceedings of the 22nd ACM International Conference on Intelligent User Interfaces (IUI 2017): Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE 2017), Limassol, Cyprus, March 2017.

[C128] Skowron, M., Lemmerich, F., Ferwerda, B., Schedl, M. Predicting Genre Preferences from Cultural and Socio-economic Factors for Music Retrieval, Proceedings of the 39th European Conference on Information Retrieval (ECIR 2017), Aberdeen, Scotland, UK, April 2017. Highlight

[C127] Ferwerda, B., Graus, M., Vall, A., Tkalčič, M., Schedl, M. How Item Discovery Enabled by Diversity Leads to Increased Recommendation List Attractiveness, Proceedings of the 32nd ACM Symposium on Applied Computing (SAC 2017), Marrakesh, Morocco, April 2017.

[C126] Ferwerda, B. and Schedl, M. Personality-Based User Modeling for Music Recommender Systems, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2016), Riva del Garda, Italy, September 2016.

[C125] Ferwerda, B., Graus, M., Vall, A., Tkalčič, M., Schedl, M. The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists, Proceedings of the 4th Workshop on Emotions and Personality in Personalized Services (EMPIRE 2016), Boston, USA, September 2016.

[C124] Ferwerda, B. and Schedl, M. Investigating the Relationship Between Diversity in Music Consumption Behavior and Cultural Dimensions: A Cross-country Analysis, Proceedings of the 24th International Conference on User Modeling, Adaptation and Personalization (UMAP 2016): Workshop on Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems (SOAP 2016), Halifax, Canada, July 2016.

[C123] Vall, A., Eghbal-Zadeh, H., Dorfer, M., Schedl, M. Timbral and Semantic Features for Music Playlists, International Conference on Machine Learning (ICML 2016): Machine Learning for Music Discovery Workshop, New York, USA, June 2016.

[C122] Schedl, M., Eghbal-Zadeh, H., Gómez, E., Tkalčič, M. An Analysis of Agreement in Classical Music Perception and Its Relationship to Listener Characteristics, Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR 2016), New York, USA, August 2016.

[C121] Gómez, E., Schedl M., Serra X., Hu X. Music Information Retrieval: Overview, Recent Developments and Future Challenges, Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR 2016), New York, USA, August 2016.

[C120] Ferwerda, B., Vall, A., Tkalčič, M., Schedl, M. Exploring Music Diversity Needs Across Countries, Proceedings of the 24th International Conference on User Modeling, Adaptation and Personalization (UMAP 2016), Halifax, Canada, July 2016.

[C119] Schedl, M., Hauger, D., Tkalčič, M., Melenhorst, M., Liem, C.C.S. A Dataset of Multimedia Material About Classical Music: PHENICX-SMM, Proceedings of the 14th International Workshop on Content-Based Multimedia Indexing (CBMI 2016), Bucharest, Romania, June 2016.

[C118] Hauger, D. and Schedl, M. Music Tweet Map: A Browsing Interface to Explore the Microblogosphere of Music, Proceedings of the 14th International Workshop on Content-Based Multimedia Indexing (CBMI 2016), Bucharest, Romania, June 2016.

[C117] Schedl, M. The LFM-1b Dataset for Music Retrieval and Recommendation, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2016), New York, USA, April 2016. Highlight

[C116] Tkalčič, M., Schedl, M., Liem, C.C.S., Melenhorst, M. Personalized Retrieval and Browsing of Classical Music and Supporting Multimedia Material, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2016), New York, USA, April 2016.

[C115] Schedl, M., Melenhorst, M., Liem, C.C.S., Dominguez, A.M., and Tkalčič, M. A Personality-based Adaptive System for Visualizing Classical Music Performances, Proceedings of the 7th ACM Multimedia Systems Conference (MMSys 2016), Klagenfurt, Austria, May 2016.

[C114] Skowron, M., Ferwerda, B., Tkalčič, M., Schedl, M. Fusing Social Media Cues: Personality Prediction from Twitter and Instagram, Proceedings of the 25th International World Wide Web Conference (WWW 2016), Montreal, Canada, April 2016. Highlight

[C113] Ferwerda, B., Schedl, M., Tkalčič, M. Personality Traits and the Relationship with (Non-) Disclosure Behavior on Facebook, Companion of the 25th International World Wide Web Conference (WWW 2016): 7th International Workshop on Modeling Social Media (MSM 2016), Montreal, Canada, April 2016.

[C112] Schedl, M. and Zhou, F. Fusing Web and Audio Predictors to Localize the Origin of Music Pieces for Geospatial Retrieval, Proceedings of the 38th European Conference on Information Retrieval (ECIR 2016), Padova, Italy, March 2016.

[C111] Ferwerda, B., Schedl, M., Tkalčič, M. Using Instagram Picture Features to Predict Users' Personality, Proceedings of the 22nd International Conference on MultiMedia Modeling (MMM 2016), Miami, USA, January 2016. Highlight

[C110] Schedl, M. Towards Personalizing Classical Music Recommendations, Proceedings of the 2nd International Workshop on Social Media Retrieval and Analysis (SoMeRA 2015), Atlantic City, USA, November 2015.

[C109] Mayr, M., Hintersteiner, T., Weingartner, M., Schröckeneder, F., Knees, P., Schedl, M. JKU-Satellite at Media Eval 2015: An Intuitive Approach to Locate Single Pictures Within a Session, Working Notes Proceedings of MediaEval 2015: Multimedia Benchmark Workshop, Wurzen, Germany, September 2015.

[C108] Weber, M., Krismayer, T., Wöß, J., Aigmüller, L., Birnzain, P., Schedl, M., Knees, P. MediaEval 2015: JKU-Tinnitus Approach to Emotion in Music Task, Working Notes Proceedings of MediaEval 2015: Multimedia Benchmark Workshop, Wurzen, Germany, September 2015.

[C107] Mironică, I., Ionescu, B., Sjöberg, M., Schedl, M., and Skowron, M. RFA at MediaEval 2015 Affective Impact of Movies Task: A Multimodal Approach, Working Notes Proceedings of MediaEval 2015: Multimedia Benchmark Workshop, Wurzen, Germany, September 2015.

[C106] Sjöberg, M., Baveye, Y., Wang, H., Quang V.L., Ionescu, B., Dellandréa, E., Schedl, M., Demarty, C.-H., Chen, L. The MediaEval 2015 Affective Impact of Movies Task, Working Notes Proceedings of MediaEval 2015: Multimedia Benchmark Workshop, Wurzen, Germany, September 2015.

[C105] Schedl, M. Listener-aware Music Search and Recommendation, Proceedings of the 6th International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015), Porto, Portugal, September 2015.

[C104] Vall, A., Skowron, M., Knees, P., Schedl, M. Improving Music Recommendations with a Weighted Factorization of the Tagging Activity, Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR 2015), Malaga, Spain, October 2015.

[C103] Eghbal-zadeh, H., Lehner, B., Schedl, M., Widmer, G. I-Vectors for Timbre-Based Music Similarity and Classification, Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR 2015), Malaga, Spain, October 2015.

[C102] Schedl, M. Listener-aware Music Recommendation from Sensor and Social Media Data, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015), Porto, Portugal, September 2015.

[C101] Eghbal-zadeh, H., Schedl, M., Widmer, G. Timbral Modeling for Music Artist Recognition Using I-vectors, Proceedings of the 23rd European Signal Processing Conference (EUSIPCO 2015), Nice, France, August-September 2015.

[C100] Liem, C.C.S., Gómez, E., Schedl, M. PHENICX: Innovating the Classical Music Experience, Proceedings of the IEEE International Conference on Multimedia and Expo (ICME 2015), Torino, Italy, June-July 2015.

[C99] Schedl, M., Sjöberg, M., Mironică, I., Ionescu, B., Quang V.L., Jiang Y.-G., Demarty, C.-H. VSD2014: A Dataset for Violent Scenes Detection in Hollywood Movies and Web Videos, Proceedings of the 13th International Workshop on Content-Based Multimedia Indexing (CBMI 2015), Prague, Czech Republic, June 2015.

[C98] Knees, P. and Schedl, M. Music Retrieval and Recommendation - A Tutorial Overview, Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015), Santiago, Chile, August 2015.

[C97] Schedl, M. and Hauger, D. Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty, Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015), Santiago, Chile, August 2015. Highlight

[C96] Ferwerda, B., Schedl, M., Tkalčič, M. Personality & Emotional States: Understanding Users' Music Listening Needs, Extended Proceedings of the 22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2015), Dublin, Ireland, June-July 2015.

[C95] Tkalčič, M., Ferwerda, B., Hauger, D., Schedl, M. Personality Correlates for Digital Concert Program Notes, Proceedings of the 22nd International Conference on User Modeling, Adaptation and Personalization (UMAP 2015), Dublin, Ireland, June-July 2015.

[C94] Ferwerda, B., Yang, E., Schedl, M., Tkalčič, M. Personality Traits Predict Music Taxonomy Preferences, ACM CHI '15 Extended Abstracts on Human Factors in Computing Systems (CHI 2015), Seoul, Republic of Korea, April 2015.

[C93] Schedl, M., Hauger, D., Farrahi, K., Tkalčič, M. On the Influence of User Characteristics on Music Recommendation, Proceedings of the 37th European Conference on Information Retrieval (ECIR 2015), Vienna, Austria, March-April 2015.

[C92] Gillhofer, M. and Schedl, M. Iron Maiden While Jogging, Debussy for Dinner? - An Analysis of Music Listening Behavior in Context, Proceedings of the 21st International Conference on MultiMedia Modeling (MMM 2015), Sydney, Australia, January 2015.

[C91] Schedl, M. and Tkalčič, M. Genre-based Analysis of Social Media Data on Music Listening Behavior, Proceedings of the 1st ACM International Workshop on Internet-Scale Multimedia Management (ISMM 2014), Orlando, USA, November 2014.

[C90] Sjöberg, M., Mironică, I., Schedl, M., Ionescu, B. FAR at MediaEval 2014 Violent Scenes Detection: A Concept-based Fusion Approach, Working Notes Proceedings of MediaEval 2014: Multimedia Benchmark Workshop, Barcelona, Spain, October 2014.

[C89] Sjöberg, M., Ionescu, B., Jiang Y.-G., Quang V.L., Schedl, M., and Demarty, C.-H. The MediaEval 2014 Affect Task: Violent Scenes Detection, Working Notes Proceedings of MediaEval 2014: Multimedia Benchmark Workshop, Barcelona, Spain, October 2014.

[C88] Farrahi, K., Schedl, M., Vall, A., Hauger, D., Tkalčič, M. Impact of Listening Behavior on Music Recommendation, Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014), Taipei, Taiwan, October 2014.

[C87] Eghbalzadeh, H. and Schedl, M. Formant Analysis of Altered Notes in a Diatonic Harmonica, Proceedings of the International Symposium on Musical Acoustics (ISMA 2014), Le Mans, France, July 2014.

[C86] Schedl, M. Social Media and Classical Music? - A first analysis within the PHENICX project: “Performances as Highly Enriched aNd Interactive Concert eXperiences”, SoMeRA'14: Proceedings of the First International Workshop on Social Media Retrieval and Analysis, Gold Coast, Australia, July 2014.

[C85] Ferwerda, B. and Schedl, M. Enhancing Music Recommender Systems with Personality Information and Emotional States: A Proposal, Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE 2014), Aalborg, Denmark, July 2014.

[C84] Tkalčič, M., Ferwerda, B., Schedl, M., Liem, C. Melenhorst, M., Odić, A., Košir, A. Using Social Media Mining for Estimating Theory of Planned Behaviour Parameters, Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE 2014), Aalborg, Denmark, July 2014.

[C83] Ferwerda, B., Schedl, M., Tkalčič, M. To Post or Not to Post: The Effects of Persuasive Cues and Group Targeting Mechanisms on Posting Behavior, Proceedings of the 6th ASE International Conference on Social Computing (SocialCom 2014), Stanford, USA, May 2014. Highlight

[C82] Schedl, M., Vall, A., Farrahi, K. User Geospatial Context for Music Recommendation in Microblogs, Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2014), Gold Coast, Australia, July 2014. Highlight

[C81] Schedl, M., Knees, P., Shen, J. SoMeRA 2014: Social Media Retrieval and Analysis Workshop, Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2014), Gold Coast, Australia, July 2014.

[C80] Demarty, C.-H., Ionescu, B., Jiang Y.-G., Quang V.L., Schedl, M., Penet C. Benchmarking Violent Scenes Detection in Movies, Proceedings of the 12th International Workshop on Content-Based Multimedia Indexing (CBMI 2014), Klagenfurt, Austria, June 2014.

[C79] Schedl, M., Breitschopf, G., Ionescu, B. Mobile Music Genius: Reggae at the Beach, Metal on a Friday Night?, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2014), Glasgow, Scotland, April 2014.

[C78] Schedl, M. and Schnitzer, D. Location-Aware Music Artist Recommendation, Proceedings of the 20th International Conference on MultiMedia Modeling (MMM 2014), Dublin, Ireland, January 2014.

[C77] Schedl, M. Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation, Proceedings of the 11th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2013), Vienna, Austria, December 2013.

[C76] Schabetsberger, C. and Schedl, M. Personalized Music Recommendation in a Mobile Environment, Proceedings of the 11th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2013), Vienna, Austria, December 2013.

[C75] Liem, C.C.S., Orio, N., Peeters, G., Schedl, M. MusiClef 2013: Soundtrack Selection for Commercials, Working Notes Proceedings of MediaEval 2013: Multimedia Benchmark Workshop, Barcelona, Spain, October 2013.

[C74] Sjöberg, M., Schlüter, J., Ionescu, B., Schedl, M. FAR at MediaEval 2013: Concept-based Violent Scenes Detection in Movies, Working Notes Proceedings of MediaEval 2013: Multimedia Benchmark Workshop, Barcelona, Spain, October 2013.

[C73] Demarty, C.-H., Pénet C., Schedl, M., Ionescu, B., Quang, V.L., and Jiang, Y.-G. The MediaEval 2013 Affect Task: Violent Scenes Detection, Working Notes Proceedings of MediaEval 2013: Multimedia Benchmark Workshop, Barcelona, Spain, October 2013.

[C72] Kaminskas, M., Ricci, F., Schedl, M. Location-aware Music Recommendation Using Auto-Tagging and Hybrid Matching, Proceedings of the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 2013. Highlight

[C71] Schedl, M., Gómez, E., Goto, M. Multimedia Information Retrieval: Music and Audio, Proceedings of the 21st ACM International Conference on Multimedia, Barcelona, Spain, October 2013.

[C70] Hauger, D., Schedl, M., Košir, A., Tkalčič, M. The Million Musical Tweets Dataset: What We Can Learn From Microblogs, Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013), Curitiba, Brazil, November 2013.

[C69] Schedl, M. and Schnitzer, D. Hybrid Retrieval Approaches to Geospatial Music Recommendation, Proceedings of the 36th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2013), Dublin, Ireland, July-August 2013. Highlight

[C68] Knees, P. and Schedl, M. Music Similarity and Retrieval, Proceedings of the 36th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2013), Dublin, Ireland, July-August 2013.

[C67] Gómez, E., Grachten, M., Hanjalic, A., Janer, J., Jordà, S., Julià, C.F., Liem, C., Martorell, A., Schedl, M., and  Widmer, G. PHENICX: Performances as Highly Enriched aNd Interactive Concert Experiences, Proceedings of the SMAC Stockholm Music Acoustics Conference 2013 and SMC Sound and Music Computing Conference 2013, Stockholm, Sweden, July-August 2013.

[C66] Ionescu, B., Schlüter, J., Mironică, I., Schedl, M. A Naïve Mid-level Concept-based Fusion Approach to Violence Detection in Hollywood Movies, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2013), Dallax, USA, 2013.

[C65] Schedl, M., Liem, C.C.S., Peeters, G., Orio, N. A Professionally Annotated and Enriched Multimodal Data Set on Popular Music, Proceedings of the 4th ACM Multimedia Systems Conference (MMSys 2013), Oslo, Norway, February-March 2013.

[C64] Schedl, M. Leveraging Microblogs for Spatiotemporal Music Information Retrieval, Proceedings of the 35th European Conference on Information Retrieval (ECIR 2013), Moscow, Russia, March 2013.

[C63] Hauger, D. and Schedl, M. Exploring Geospatial Music Listening Patterns in Microblog Data, Proceedings of the 10th International Workshop on Adaptive Multimedia Retrieval (AMR 2012), Copenhagen, Denmark, October 2012.

[C62] Seyerlehner, K., Sonnleitner, R., Schedl, M., Hauger, D., and Ionescu, B. From Improved Auto-taggers to Improved Music Similarity Measures, Proceedings of the 10th International Workshop on Adaptive Multimedia Retrieval (AMR 2012), Copenhagen, Denmark, October 2012.

[C61] Liem, C.C.S., Orio, N., Peeters, G., Schedl, M. Brave New Task: Musiclef Multimodal Music Tagging, Working Notes Proceedings of MediaEval 2012: Multimedia Benchmark Workshop, Pisa, Italy, October 2012.

[C60] Schlüter, J., Ionescu, B., Mironică, I., Schedl, M. ARF @ MediaEval 2012: An Uninformed Approach to Violence Detection in Hollywood Movies, Working Notes Proceedings of MediaEval 2012: Multimedia Benchmark Workshop, Pisa, Italy, October 2012.

[C59] Ionescu, B., Mironică, I., Seyerlehner, K., Knees, P., Schlüter, J., Schedl, M., Cucu, H., Buzo, A., Lambert, P. ARF @ MediaEval 2012: Multimodal Video Classification, Working Notes Proceedings of MediaEval 2012: Multimedia Benchmark Workshop, Pisa, Italy, October 2012.

[C58] Schedl, M. and Flexer, A. Putting the User in the Center of Music Information Retrieval, Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR 2012), Porto, Portugal, October 2012. Highlight

[C57] Böck, S., Krebs, F., Schedl, M. Evaluating the Online Capabilities of Onset Detection Methods, Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR 2012), Porto, Portugal, October 2012.

[C56] Urbano, J., Downie, J.S., McFee, B., Schedl, M. How Significant is Statistically Significant? The Case of Audio Music Similarity and Retrieval, Proceedings of the 13th International Society for Music Information Retrieval Conference (ISMIR 2012), Porto, Portugal, October 2012. Highlight

[C55] Orio, N., Liem, C.C.S., Peeters, G., Schedl, M. MusiClef: Multimodal Music Tagging Task, Proceedings of the 3rd Conference on Multilingual and Multimodal Information Access Evaluation (CLEF 2012), Rome, Italy, September 2012.

[C54] Böck, S., Arzt, A., Krebs, F., Schedl, M. Online Real-time Onset Detection with Recurrent Neural Networks, Proceedings of the 15th International Conference on Digital Audio Effects (DAFx 2012), York, UK, September 2012.

[C53] Huber, S., Schedl, M., Knees, P. nepDroid: An Intelligent Mobile Music Player, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2012), Hong Kong, China, June 2012.

[C52] Schedl, M. and Hauger, D. Mining Microblogs to Infer Music Artist Similarity and Cultural Listening Patterns, Proceedings of the 21st International World Wide Web Conference (WWW 2012): 4th International Workshop on Advances in Music Information Research (AdMIRe 2012), Lyon, France, April 2012.

[C51] Urbano, J. and Schedl, M. Towards Minimal Test Collections for Evaluation of Audio Music Similarity and Retrieval, Proceedings of the 21st International World Wide Web Conference (WWW 2012): 4th International Workshop on Advances in Music Information Research (AdMIRe 2012), Lyon, France, April 2012.

[C50] Schedl, M., Hauger, D., Schnitzer, D. A Model for Serendipitous Music Retrieval, Proceedings of the 16th International Conference on Intelligent User Interfaces (IUI 2012): 2nd International Workshop on Context-awareness in Retrieval and Recommendation (CaRR 2012), Lisbon, Portugal, February 2012.

[C49] Böck, S. and Schedl, M. Polyphonic Piano Note Transcription with Recurrent Neural Networks, Proceedings of the 37th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2012), Kyoto, Japan, March 2012. Highlight

[C48] Knees, P. and Schedl, M. Towards Semantic Music Information Extraction from the Web Using Rule Patterns and Supervised Learning, Proceedings of the 2nd Workshop on Music Recommendation and Discovery (WOMRAD 2011), Chicago, IL, USA, October 2011.

[C47] Cantador, I., Cortizo, J. C., Carrero, F. M., Troyano, J. A., Rosso, P., Schedl, M. Overview of the Third International Workshop on Search and Mining User-generated Contents, Proceedings of the 20th ACM International Conference on Information and Knowledge Management (CIKM 2011), Glasgow, Scotland, October 2011.

[C46] Schedl, M., Knees, P., Böck, S. Investigating the Similarity Space of Music Artists on the Micro-Blogosphere, Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, FL, USA, October 2011.

[C45] Schnitzer, D., Flexer, A., Schedl, M., Widmer, G. Using Mutual Proximity to Improve Content-Based Audio Similarity, Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, FL, USA, October 2011.

[C44] Orio, N., Rizo, D., Miotto, R., Montecchio, N., Schedl, M., and Lartillot, O. MusiCLEF: A Benchmark Activity in Multimodal Music Information Retrieval, Proceedings of the 12th International Society for Music Information Retrieval Conference (ISMIR 2011), Miami, FL, USA, October 2011.

[C43] Schedl, M. and Knees, P. Personalization in Multimodal Music Retrieval, Proceedings of the 9th Workshop on Adaptive Multimedia Retrieval (AMR 2011), Barcelona, Spain, July 2011.

[C42] Böck, S. and Schedl, M. Enhanced Beat Tracking with Context-Aware Neural Networks, Proceedings of the 14th International Conference on Digital Audio Effects (DAFx 2011), Paris, France, September 2011.

[C41] Schedl, M. Analyzing the Potential of Microblogs for Spatio-Temporal Popularity Estimation of Music Artists, Proceedings of the IJCAI 2011: International Workshop on Social Web Mining, Barcelona, Spain, July 2011. Highlight

[C40] Schedl, M., Höglinger, C., Knees, P. Large-Scale Music Exploration in Hierarchically Organized Landscapes Using Prototypicality Information, Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR 2011), Trento, Italy, April 2011. Highlight

[C39] Seyerlehner, K., Widmer, G., Schedl, M., Knees, P. Automatic Music Tag Classification based on Block-Level Features, Proceedings of the 7th Sound and Music Computing Conference (SMC 2010), Barcelona, Spain, July 2010.

[C38] Schedl, M., Pohle, T., Koenigstein, N., Knees, P. What's Hot? Estimating Country-Specific Artist Popularity, Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, the Netherlands, August 2010. Highlight

[C37] Schedl, M. On the Use of Microblogging Posts for Similarity Estimation and Artist Labeling, Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, the Netherlands, August 2010. Highlight

[C36] Knees, P., Schedl, M., Pohle, T., Seyerlehner, K., Widmer, G. Supervised and Unsupervised Web Document Filtering Techniques to Improve Text-Based Music Retrieval, Proceedings of the 11th International Society for Music Information Retrieval Conference (ISMIR 2010), Utrecht, the Netherlands, August 2010.

[C35] Schedl, M., Schiketanz, C., Seyerlehner, K. Country of Origin Determination via Web Mining Techniques, Proceedings of the IEEE International Conference on Multimedia and Expo (ICME 2010): 2nd International Workshop on Advances in Music Information Research (AdMIRe 2010), Singapore, July 2010.

[C34] Schedl, M., Seyerlehner, K., Schnitzer, D., Widmer, G., and Schiketanz, C. Three Web-based Heuristics to Determine a Person's or Institution's Country of Origin, Proceedings of the 33th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2010), Geneva, Switzerland, July 2010. Highlight

[C33] Schedl, M. and Knees, P. Context-based Music Similarity Estimation, Proceedings of the 3rd International Workshop on Learning the Semantics of Audio Signals (LSAS 2009), Graz, Austria, December 2009.

[C32] Knees, P., Pohle, T., Schedl, M., Schnitzer, D., Seyerlehner, K., Widmer, G. Augmenting Text-Based Music Retrieval with Audio Similarity, Proceedings of the 10th International Conference on Music Information Retrieval (ISMIR 2009), Kobe, Japan, October 2009.

[C31] Pohle, T., Schnitzer, D., Schedl, M., Knees, P., Widmer, G. On Rhythm and General Music Similarity, Proceedings of the 10th International Conference on Music Information Retrieval (ISMIR 2009), Kobe, Japan, October 2009.

[C30] Grachten, M., Schedl, M., Pohle, T., Widmer, G. The ISMIR Cloud: A Decade of ISMIR Conferences at Your Fingertips, Proceedings of the 10th International Conference on Music Information Retrieval (ISMIR 2009), Kobe, Japan, October 2009.

[C29] Schedl, M. and Pohle, T. Exploring Music Artists via Descriptive Terms and Multimedia Content, Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies (SAMT 2008), Koblenz, Germany, December 2008.

[C28] Dopler, M., Schedl, M., Pohle, T., Knees, P. Accessing Music Collections via Representative Cluster Prototypes in a Hierarchical Organization Scheme, Proceedings of the 9th International Conference on Music Information Retrieval (ISMIR 2008), Philadelphia, PA, USA, September 2008.

[C27] Knees, P., Schedl, M., Pohle, T. A Deeper Look into Web-based Classification of Music Artists, Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS 2008), Paris, France, June 2008.

[C26] Schedl, M. and Knees, P. Investigating Different Term Weighting Functions for Browsing Artist-Related Web Pages by Means of Term Co-Occurrences, Proceedings of the 2nd Workshop on Learning the Semantics of Audio Signals (LSAS 2008), Paris, France, June 2008.

[C25] Schedl, M., Knees, P., Pohle, T., Widmer, G. Towards an Automatically Generated Music Information System via Web Content Mining, Proceedings of the 30th European Conference on Information Retrieval (ECIR 2008), Glasgow, Scotland, March-April 2008. Highlight

[C24] Knees, P., Pohle, T., Schedl, M., Schnitzer, D., Seyerlehner K. A Document-centered Approach to a Natural Language Music Search Engine, Proceedings of the 30th European Conference on Information Retrieval (ECIR 2008), Glasgow, Scotland, March-April 2008.

[C23] Schedl, M., Knees, P., Widmer, G., Seyerlehner, K., Pohle, T. Browsing the Web Using Stacked Three-Dimensional Sunbursts to Visualize Term Co-Occurrences and Multimedia Content, Proceedings of the IEEE Visualization 2007 Conference (Vis 2007), Sacramento, California, USA, October 2007. Highlight

[C22] Geleijnse, G., Schedl, M., Knees, P. The Quest for Ground Truth in Musical Artist Tagging in the Social Web Era, Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, September 2007.

[C21] Pohle, T., Knees, P., Schedl, M., Widmer, G. Meaningfully Browsing Music Services, Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, September 2007.

[C20] Schedl, M., Widmer, G., Pohle, T., Seyerlehner, K. Web-based Detection of Music Band Members and Line-Up, Proceedings of the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, Austria, September 2007.

[C19] Seyerlehner, K., Pohle, T., Schedl, M., Widmer, G. Automatic Music Detection in Television Productions, Proceedings of the 10th International Conference on Digital Audio Effects (DAFx 2007), Bordeaux, France, September 2007.

[C18] Schedl, M. and Widmer, G. Automatically Detecting Members and Instrumentation of Music Bands via Web Content Mining, Proceedings of the 5th Workshop on Adaptive Multimedia Retrieval (AMR 2007), Paris, France, July 2007.

[C17] Knees, P., Pohle, T., Schedl, M., Widmer, G. A Music Search Engine Built upon Audio-based and Web-based Similarity Measures, Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2007), Amsterdam, the Netherlands, July 2007. Highlight

[C16] Pohle, T., Knees, P., Schedl, M., Widmer, G. Building an Interactive Next-Generation Artist Recommender Based on Automatically Derived High-Level Concepts, Proceedings of the 5th International Workshop on Content-Based Multimedia Indexing (CBMI 2007), Bordeaux, France, June 2007.

[C15] Schedl, M., Knees, P., Seyerlehner, K., Pohle, T. The CoMIRVA Toolkit for Visualizing Music-Related Data, Proceedings of the 9th Eurographics/IEEE VGTC Symposium on Visualization (EuroVis 2007), Norrköping, Sweden, May 2007.

[C14] Knees, P., Pohle, T., Schedl, M., Widmer, G. Automatically Describing Music on a Map, Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals (LSAS 2006), Athens, Greece, December 2006.

[C13] Pohle, T., Schedl, M., Knees, P., Widmer, G. Automatically Adapting the Structure of Audio Similarity Spaces, Proceedings of the 1st Workshop on Learning the Semantics of Audio Signals (LSAS 2006), Athens, Greece, December 2006.

[C12] Schedl, M., Knees, P., Widmer, G. Investigating Web-Based Approaches to Revealing Prototypical Music Artists in Genre Taxonomies, Proceedings of the 1st IEEE International Conference on Digital Information Management (ICDIM 2006), Bangalore, India, December 2006.

[C11] Knees, P., Pohle, T., Schedl, M., Widmer, G. Combining Audio-based Similarity with Web-based Data to Accelerate Automatic Music Playlist Generation, Proceedings of the 8th ACM SIGMM International Workshop on Multimedia Information Retrieval (MIR 2006), Santa Barbara, California, USA, October 2006.

[C10] Knees, P., Schedl, M., Pohle, T., Widmer, G. An Innovative Three-Dimensional User Interface for Exploring Music Collections Enriched with Meta-Information from the Web, Proceedings of the ACM Multimedia 2006, Santa Barbara, California, USA, October 2006. Runner-up for Best Paper Award Highlight

[C9] Pohle, T., Schedl, M., Knees, P., Widmer, G. Independent Component Analysis for Music Similarity Computation, Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, October 2006.

[C8] Schedl, M., Pohle, T., Knees, P., Widmer, G. Assigning and Visualizing Music Genres by Web-based Co-Occurrence Analysis, Proceedings of the 7th International Conference on Music Information Retrieval (ISMIR 2006), Victoria, Canada, October 2006.

[C7] Schedl, M., Knees, P., Pohle, T., Widmer, G. Towards Automatic Retrieval of Album Covers, Proceedings of the 28th European Conference on Information Retrieval (ECIR 2006), London, UK, April 2006.

[C6] Schedl, M., Knees, P., Widmer, G. Interactive Poster: Using CoMIRVA for Visualizing Similarities Between Music Artists, Proceedings of the IEEE Visualization 2005 (Vis 2005), Minneapolis, Minnesota, USA, October 2005.

[C5] Schedl, M., Knees, P., Widmer, G. Improving Prototypical Artist Detection by Penalizing Exorbitant Popularity, Proceedings of the 3rd International Symposium on Computer Music Modeling and Retrieval (CMMR 2005), Pisa, Italy, September 2005.

[C4] Schedl, M., Knees, P., Widmer, G. Discovering and Visualizing Prototypical Artists by Web-based Co-Occurrence Analysis, Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, UK, September 2005.

[C3] Knees, P., Schedl, M., Widmer, G. Multiple Lyrics Alignment: Automatic Retrieval of Song Lyrics, Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), London, UK, September 2005.

[C2] Widmer, G., Dixon, S., Flexer, A., Goebl, W., Madsen, S.T., Pampalk, E., Pohle, T., Schedl, M., Tobudic, A. Studio Report: The Machine Learning and Intelligent Music Processing Group at the Austrian Research Institute for Artificial Intelligence (OFAI), Proceedings of the 2005 International Computer Music Conference (ICMC 2005), Barcelona, Spain, September 2005.

[C1] Schedl, M., Knees, P., Widmer, G. A Web-Based Approach to Assessing Artist Similarity using Co-Occurrences, Proceedings of the 4th International Workshop on Content-Based Multimedia Indexing (CBMI 2005), Riga, Latvia, June 2005.
Books and Book Chapters (peer-reviewed)

[B12] Kowald, D., Reiter-Haas, M., Kopeinik, S., Schedl, M., Lex, E. Transparent Music Preference Modeling and Recommendation with a Model of Human Memory Theory, In Bruce Ferwerda, Mark Graus, Panagiotis Germanakos, Marko Tkalčič (eds.), A Human-Centered Perspective of Intelligent Personalized Environments and Systems, Springer, 2024.

[B11] Schedl, M. and Lex, E. Fairness of Information Access Systems, In Mirjam Augstein, Eelco Herder, Wolfgang Wörndl (eds.), Personalized Human-Computer Interaction (2nd edition), DeGruyter, 2023.

[B10] Knees, P., Schedl, M., Ferwerda, B., Laplante, A. Listener Awareness in Music Recommender Systems: Directions and Current Trends, In Mirjam Augstein, Eelco Herder, Wolfgang Wörndl (eds.), Personalized Human-Computer Interaction (2nd edition), DeGruyter, 2023.

[B9] Deldjoo, Y., Schedl, M., Hidasi, B., Wei, Y., He, X. Multimedia Recommender Systems: Algorithms and Challenges, In Francesco Ricci, Lior Rokach, Bracha Shapira (eds.), Recommender Systems Handbook (3rd edition), Springer, 2022.

[B8] Schedl, M., Knees, P., McFee, B., Bogdanov, D. Music Recommendation Systems: Techniques, Use Cases, and Challenges, In Francesco Ricci, Lior Rokach, Bracha Shapira (eds.), Recommender Systems Handbook (3rd edition), Springer, 2022.

[B7] Knees, P., Schedl, M., Ferwerda, B., Laplante, A. User Awareness in Music Recommender Systems, In Mirjam Augstein, Eelco Herder, Wolfgang Wörndl (eds.), Personalized Human-Computer Interaction, DeGruyter, 2019.

[B6] Knees, P. and Schedl, M. Music Similarity and Retrieval: Introduction to Audio- and Web-based Strategies, Springer, 2016.

[B5]  Schedl, M., Knees, P., McFee, B., Bogdanov, D., and Kaminskas, M. Music Recommender Systems, In Francesco Ricci, Lior Rokach, Bracha Shapira (eds.), Recommender Systems Handbook (2nd edition), Springer, 2015.

[B4] Schedl, M., Sordo, M., Koenigstein, N., Weinsberg, U. Mining User-generated Data for Music Information Retrieval, In Marie-Francine Moens, Juanzi Li, Tat-Seng Chua (eds.), Mining of User Generated Content and Its Applications, CRC Press, 2014.

[B3] Schedl, M. Exploiting Social Media for Music Information Retrieval, In Naeem Ramzan, Roelof van Zwol, Jong-Seok Lee, Kai Clüver, Xian-Sheng Hua (eds.), Social Media Retrieval, Springer, 2012.

[B2] Schedl, M., Stober, S., Gómez, E., Orio, N., Liem, C.C.S. User-Aware Music Retrieval, In Meinard Müller, Masataka Goto, Markus Schedl (eds.), Multimodal Music Processing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Saarbrücken/Wadern, Germany, 2012.

[B1] Schedl, M. Web- and Community-based Music Information Extraction, In Tao Li, Mitsunori Ogihara, George Tzanetakis (eds.), Music Data Mining, CRC Press/Chapman Hall, July 2011.

Other Publications (non-peer-reviewed)

[O4] Seyerlehner, K. and Schedl, M. MIREX 2014: Optimizing the Fluctuation Pattern Extraction Process, Extended Abstract to the Music Information Retrieval Evaluation eXchange (MIREX 2014), Taipei, Taiwan, October 2014.

[O3] Seyerlehner, K., Schedl, M., Knees, P., Sonnleitner, R. A Refined Block-Level Feature Set for Classification, Similarity and Tag Prediction, Extended Abstract to the Music Information Retrieval Evaluation eXchange (MIREX 2011), Miami, FL, USA, October 2011.

[O2] Seyerlehner, K., Schedl, M., Pohle, T., Knees, P. Using Block-Level Features for Genre Classification, Tag Classification, and Music Similarity Estimation, Extended Abstract to the Music Information Retrieval Evaluation eXchange (MIREX 2010), Utrecht, the Netherlands, August 2010.

[O1] Seyerlehner, K. and Schedl, M. Block-Level Audio Features for Music Genre Classification, Extended Abstract to the Music Information Retrieval Evaluation eXchange (MIREX 2009), Kobe, Japan, October 2009.

Theses

[T3] Schedl, M. On the Use of the Web and Social Media in Multimodal Music Information Retrieval, Postdoctoral Thesis (Habilitation), Johannes Kepler University Linz, May 2013.

[T2] Schedl, M. Automatically Extracting, Analyzing, and Visualizing Information on Music Artists from the World Wide Web, PhD Thesis, Johannes Kepler University Linz, June 2008.

[T1] Schedl, M. An Explorative, Hierarchical User Interface to Structured Music Repositories, Master's Thesis, Vienna University of Technology, December 2003.

Last update: November 2024