About
Eva Zangerle is a Professor at Universität Innsbruck, Austria, with a focus on recommender systems, music information retrieval, and data science. She actively contributes to multi-method evaluation frameworks and collaborative research initiatives like PAN (Plagiarism Authorship Verification) workshops.
- Key research areas: Recommender Systems Evaluation, Music Emotion Recognition, Authorship Analysis
- Major collaborations with institutions like Zenodo, ACM, CEUR-WS.org, and RecSys conferences
Her recent work explores graph neural networks for music recommendation, style change detection in multi-author texts, and cross-domain user modeling. Articles emphasize temporal modeling, multimodal data fusion, and ethical considerations in algorithmic systems.
Eva leads tasks in PAN workshops and contributes to open-access datasets. She collaborates with researchers like Christine Bauer, Alan Said, and Günther Specht on improving evaluation practices in recommender systems.
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