Eva Zangerle

Ass.-Prof. Priv.-Doz. 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. She recently 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

2020

Bib Link Download

Eva Zangerle, Martin Pichl and Markus Schedl: User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues. In Transactions of the International Society for Music Information Retrieval, vol. 3, no. 1. Ubiquity Press, 2020

Bib Link Download

Meijun Liu, Eva Zangerle, Xiao Hu, Alessandro Melchiorre and Markus Schedl: Pandemics, Music, and Collective Sentiment: Evidence from the Outbreak of COVID-19. In Proceedings of the 21st International Society for Music Information Retrieval Conference 2020 (ISMIR 2020), pages 157-165. 2020

Bib Link Download

Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020

Bib Link Download

Eva Zangerle, Maximilian Mayerl, Günther Specht, Martin Potthast and Benno Stein: Overview of the style change detection task at PAN 2020. In CLEF 2020 Working Notes, CEUR Workshop Proceedings 2696, Paper 256. 9 S. 2020

Bib Link Download

Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso and others: Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection. In International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2020), pages 372-383. 2020.

Bib Link Download

Clemens Hörtenhuemer and Eva Zangerle: A Multi-Aspect Classification Ensemble Approach for Profiling Fake News Spreaders on Twitter. In Proceedings of the International Conference and Labs of the Evaluation Forum (CLEF), Thessaloniki, Greece, pages 22-25. 2020.

Bib Link Download

Alessandro B. Melchiorre, Eva Zangerle and Markus Schedl: Personality Bias of Music Recommendation Algorithms. In 14th ACM Conference on Recommender Systems (RecSys 2020), pages 533–538. ACM, 2020.

Bib Link Download

Maximilian Mayerl, Michael Vötter, Manfred Moosleitner and Eva Zangerle: Comparing Lyrics Features for Genre Recognition. In Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), pages 73-77. 2020.

2019

Bib Link Download

Asir Saeed, Suzana Ilic and Eva Zangerle: Creating GANs for generating poems, lyrics and metaphors. In NeurIPS Machine Learning for Creativity and Design Workshop, 2019

Bib Link Download

Eva Zangerle, Ramona Huber, Michael Vötter and Yi-Hsuan Yang: Hit Song Prediction: Leveraging Low- and High-Level Audio Features. In Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019), pages 319-326. 2019

Bib Link Download

Christine Bauer and Eva Zangerle: Leveraging Multi-Method Evaluation for Multi-Stakeholder Settings. In Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). ceur-ws.org, 2019

Bib Link Download

Walter Daelemans, Mike Kestemont, Enrique Manjavacas, Martin Potthast, Francisco M. Rangel Pardo, Paolo Rosso, Günther Specht, Efstathios Stamatatos, Benno Stein, Michael Tschuggnall, Matti Wiegmann and Eva Zangerle: Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-Domain Authorship Attribution and Style Change Detection. In Experimental IR Meets Multilinguality, Multimodality, and Interaction - 10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9-12, 2019, Proceedings, vol. 11696, pages 402-416.

Bib Link Download

Eva Zangerle, Michael Tschuggnall, Günther Specht, Martin Potthast and Benno Stein: Overview of the Style Change Detection Task at PAN 2019. In CLEF 2019 Labs and Workshops, Notebook Papers. CEUR-WS.org, 2019

Bib Link Download

Manuel Schmidt and Eva Zangerle: Article Quality Classification on Wikipedia: Introducing Document Embeddings and Content Features. In Proceedings of the 15th International Symposium on Open Collaboration, OpenSym 2019, Skövde, Sweden, August 20-22, 2019, pages 13:1-13:8. ACM, 2019

Bib Link Download

Maximilian Mayerl, Michael Vötter, Eva Zangerle and Günther Specht: Language Models for Next-Track Music Recommendation. In Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, Germany, June 11-14, 2019., pages 15-19. 2019

Bib Link Download

Michael Vötter, Eva Zangerle, Maximilian Mayerl and Günther Specht: Autoencoders for Next-Track-Recommendation. In Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg, Germany, June 11-14, 2019., pages 20-25. 2019

Bib Link

Gerald Hiebel, Klaus Hanke, Claudia Posch, Gerhard Rampl, Elisabeth Gruber, Andrea Mussmann and Eva Zangerle: Zur Identifikation und Verortung von Bergnamen in alpiner Literatur. In 20. Internationale Geodätische Woche Obergurgl 2019, pages 91-100. VDE Verlag, 2019

Bib Link Download

Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Boyu Chen, Yi-Hsuan Yang and Eva Zangerle: Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.

Bib Link Download

Hsiao-Tzu Hung, Yu-Hua Chen, Maximilian Mayerl, Michael Vötter, Eva Zangerle and Yi-Hsuan Yang: MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.

2018

Bib Link

Bettina Larl and Eva Zangerle: Leiwand Oida: Geolocating Regional Linguistic Variation of German on Twitter. In Proceedings of the 6th Conference on Computer-Mediated Communication (CMC) and Social Media Corpora (CMC-corpora 2018). 2018