Eva Zangerle

Ass.-Prof. Dr. Eva Zangerle

Tel: +43 512 507 53236
Office
ICT building, 2nd floor, room 3W02
Consultation Hours
schedule meeting here

Eva is an assistant professor at the Department of Computer Science at the University of Innsbruck, Austria. Her primary scientific interests focus on (context-aware) recommender systems and user modeling aspects of music information retrieval tasks. She earned her Ph.D. from the University of Innsbruck in the field of recommender systems for collaborative social media platforms. During her postdoc, she did short-term research stays at Ritsumeikan University in Kyoto, Japan (funded by a Postdoctoral Fellowship for Overseas Researchers from the Japan Society for the Promotion of Science), Freie Universität Berlin, Germany (funded by the Global Faculty Program of Freie Universität) and Johannes-Kepler-Universität Linz, Austria.

Eva is also co-author of a book on MySQL (currently in it’s 3rd edition). For more information on the book, visit Rheinwerk Verlag (the publisher) or the book’s website .

Publications

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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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, Berta Chulvi, Elisabetta Fersini, Annina Heini, Mike Kestemont, Krzysztof Kredens, Maximilian Mayerl, Reynier 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, and Style Change Detection.

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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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Eva Zangerle and Christine Bauer: Evaluating Recommender Systems: Survey and Framework. In ACM Comput. Surv.. Association for Computing Machinery, 2022 Just Accepted

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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, Virtual Event, September 21-24, 2021, Proceedings, vol.

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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

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Janek Bevendorff, BERTa Chulvi, Gretel Liz De La Pe\~na Sarrac\'en, 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 Advances in Information Retrieval. ECIR 2021, pages 567-573. Springer International Publishing, 2021

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Eva Zangerle, Chih-Ming Chen, Ming-Feng Tsai and Yi-Hsuan Yang: Leveraging Affective Hashtags for Ranking Music Recommendations. In IEEE Transactions on Affective Computing, vol. 12, no. 1, pages 78-91. 2021

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Dominik Kowald, Peter Muellner, Eva Zangerle, Christine Bauer, Markus Schedl and Elisabeth Lex: Support the underground: characteristics of beyond-mainstream music listeners. In EPJ Data Science, vol. 10, no. 1, pages 1-26. Springer, 2021