Eva Zangerle

Assoc. Prof. Dr. Eva Zangerle

eva.zangerle [at] uibk.ac.at
Scientific Staff
Tel: +43 512 507 53236
Office
ICT building, 2nd floor, room 3W02
Consultation Hours
schedule meeting here

Eva is an associate professor at the Department of Computer Science at the University of Innsbruck, Austria. She was awarded the habilitation degree (venia docendi) in Computer Science in 2023 (title of thesis: "Recommender Systems for Music Retrieval Tasks"). In 2013, Eva earned her Ph.D. from the University of Innsbruck, focusing on recommender systems for collaborative social media platforms. She has expanded her research horizons by undertaking short-term research stays at Ritsumeikan University in Kyoto, Japan, Freie Universität Berlin, Germany, and Johannes Kepler University Linz, Austria.

Eva's primary scientific interests revolve around the field of recommender systems, particularly their evaluation and user modeling, particularly within the domain of music information retrieval. Eva has been honored with the Women in RecSys Best Journal Paper of the Year award in both 2022 and 2023. Eva is one of the organizers of the PERSPECTIVES workshop series "Perspectives on the Evaluation of Recommender Systems".

In addition to her scholarly endeavors, Eva is also a co-author of a book on MySQL, which is currently in its third edition. 

Publications

2023

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Janek Bevendorff, Mara Chinea-Rios, Marc Franco-Salvador, Annina Heini, Erik Körner, Krzysztof Kredens, Maximilian Mayerl, Piotr Pkezik, Martin Potthast, Francisco Rangel, Paolo Rosso, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, Magdalena Wolska and Eva Zangerle: Overview of PAN 2023: Authorship Verification, Multi-author Writing Style Analysis, Profiling Cryptocurrency Influencers, and Trigger Detection. In Advances in Information Retrieval (ECIR 2023), pages 518-526. Springer Nature Switzerland, 2023

2022

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Eva Zangerle: Recommender Systems for Music Retrieval Tasks. Habilitation Thesis, University of Innsbruck, 2022

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Maximilian Mayerl, Stefan Brandl, Günther Specht, Markus Schedl and Eva Zangerle: Verse versus Chorus: Structure-aware Feature Extraction for Lyrics-based Genre Recognition. In Proceedings of the 23rd International Society for Music Information Retrieval Conference 2022, pages 884-890. ISMIR, 2022

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Marta Moscati, Emilia Parada-Cabaleiro, Yashar Deldjoo, Eva Zangerle and Markus Schedl: Music4All-Onion - A Large-Scale Multi-Faceted Content-Centric Music Recommendation Dataset. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management, pages 4339–4343. Association for Computing Machinery, 2022

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Eva Zangerle, Christine Bauer and Alan Said: Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2022, co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022). Vol. 3228. CEUR-WS.org, 2022

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Andreas Peintner, Marta Moscati, Emilia Parada-Cabaleiro, Markus Schedl and Eva Zangerle: Unsupervised Graph Embeddings for Session-based Recommendation with Item Features. In CARS: Workshop on Context-Aware Recommender Systems (RecSys ’22). 2022

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Eva Zangerle, Christine Bauer and Alan Said: Second Workshop: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2022). In Proceedings of the 16th ACM Conference on Recommender Systems, pages 652–653. Association for Computing Machinery, 2022

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Janek Bevendorff et al.: Overview of PAN 2022: Authorship Verification, Profiling Irony and Stereotype Spreaders, and Style Change Detection. In Experimental IR Meets Multilinguality, Multimodality, and Interaction - 13th International Conference of the CLEF Association, CLEF 2022, Bologna, Italy, September 5-8, 2022, Proceedings, vol. 13390, pages 382-394. Springer, 2022

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Eva Zangerle, Maximilian Mayerl, Martin Potthast and Benno Stein: Overview of the Style Change Detection Task at PAN 2022. In Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, vol. 3180, pages 2344-2356. CEUR-WS.org, 2022

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Janek Bevendorff, Berta Chulvi, Elisabetta Fersini, Annina Heini, Mike Kestemont, Krzysztof Kredens, Maximilian Mayerl, Reyner Ortega-Bueno, Piotr Pezik, Martin Potthast, Francisco Rangel, Paolo Rosso, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, Magdalena Wolska and Eva Zangerle: Overview of PAN 2022: Authorship Verification, Profiling Irony and Stereotype Spreaders, Style Change Detection, and Trigger Detection. In Advances in Information Retrieval. ECIR 2022., pages 331-338. Springer International Publishing, 2022

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Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht and Viktor Leis: Height Optimized Tries. In ACM Trans. Database Syst., vol. 47, no. 1. Association for Computing Machinery, 2022

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Eva Zangerle, Christine Bauer and Alan Said: Report on the 1st Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2021) at RecSys 2021. In SIGIR Forum, vol. 55, no. 2. Association for Computing Machinery, 2022

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Manfred Moosleitner, Günther Specht and Eva Zangerle: Co-rating Attacks on Recommendation Algorithms. In Proceedings of the 32nd GI-Workshop Grundlagen von Datenbanksysteme (GvDB'21) . 2022

2021

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Maximilian Mayerl, Michael Vötter, Andreas Peintner, Günther Specht and Eva Zangerle: Recognizing Song Mood and Theme: Clustering-based Ensembles. In Working Notes Proceedings of the MediaEval 2021 Workshop. ceur-ws.org, 2021

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Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: Novel Datasets for Evaluating Song Popularity Prediction Tasks. In IEEE International Symposium on Multimedia, ISM 2021, Virtual Event, November 29 - December 1, 2021, pages 166-173. IEEE, 2021

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Eva Zangerle , Christine Bauer and Alan Said: Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021, co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021). Vol. 2955. CEUR-WS.org, 2021

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Eva Zangerle, Maximilian Mayerl, Martin Potthast and Benno Stein: Overview of the Style Change Detection Task at PAN 2021. In CLEF 2021 Labs and Workshops, Notebook Papers, pages 1760-1771. CEUR-WS.org, 2021

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Janek Bevendorff, Berta Chulvi, Gretel Liz De la Pena Sarracen, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, Magdalena Wolska and Eva Zangerle: Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection. In Experimental IR Meets Multilinguality, Multimodality, and Interaction - 12th International Conference of the CLEF Association, CLEF 2021, Proceedings, vol. 12880, pages 419-431. Springer, 2021

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Eva Zangerle, Christine Bauer and Alan Said: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES). In Fifteenth ACM Conference on Recommender Systems, pages 794–795. Association for Computing Machinery, 2021

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Martin Pichl and Eva Zangerle: User models for multi-context-aware music recommendation. In Multimedia Tools and Applications, vol. 80, no. 15, pages 22509-22531. Springer, 2021