Dr. Eva Zangerle

@inproceedings{ecir20_pan,
 abstract = {The paper gives a brief overview of the four shared tasks that are to be organized at the PAN 2020 lab on digital text forensics and stylometry, hosted at CLEF conference. The tasks include author profiling, celebrity profiling, cross-domain author verification, and style change detection, seeking to advance the state of the art and to evaluate it on new benchmark datasets.},
 address = {Cham},
 author = {Bevendorff, Janek
and Ghanem, Bilal
and Giachanou, Anastasia
and Kestemont, Mike
and Manjavacas, Enrique
and Potthast, Martin
and Rangel, Francisco
and Rosso, Paolo
and Specht, Günther
and Stamatatos, Efstathios
and Stein, Benno
and Wiegmann, Matti
and Zangerle, Eva},
 booktitle = {Advances in Information Retrieval},
 editor = {Jose, Joemon M.
and Yilmaz, Emine
and Magalhães, João
and Castells, Pablo
and Ferro, Nicola
and Silva, Mário J.
and Martins, Flávio},
 isbn = {978-3-030-45442-5},
 pages = {508--516},
 publisher = {Springer International Publishing},
 title = {Shared Tasks on Authorship Analysis at PAN 2020},
 year = {2020}
}

@article{zangerle2020user,
  title={User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues},
  author={Zangerle, Eva and Pichl, Martin and Schedl, Markus},
  journal={Transactions of the International Society for Music Information Retrieval},
  volume={3},
  number={1},
  year={2020},
  publisher={Ubiquity Press},
  doi={10.5334/tismir.37}
}

@inproceedings{mediaeval19_inn,
 author = {Maximilian Mayerl and Michael Vötter and Hsiao-Tzu Hung and Boyu Chen and Yi-Hsuan Yang and Eva Zangerle},
 booktitle = {Working Notes Proceedings of the MediaEval 2019 Workshop},
 month = {12},
 publisher = {ceur-ws.org},
 title = {Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks},
 year = {2020}
}

@inproceedings{mediaeval19_tai,
 author = {Hsiao-Tzu Hung and Yu-Hua Chen and Maximilian Mayerl and Michael Vötter and Eva Zangerle and Yi-Hsuan Yang},
 booktitle = {Working Notes Proceedings of the MediaEval 2019 Workshop},
 month = {12},
 publisher = {ceur-ws.org},
 title = {MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach},
 year = {2019}
}

@inproceedings{neurips_creativity19,
title = {{Creating GANs for generating poems, lyrics and metaphors}},
author = {Asir Saeed and Suzana Ilic and Eva Zangerle},
year = {2019},
booktitle = {{NeurIPS Machine Learning for Creativity and Design Workshop},
url = {https://neurips2019creativity.github.io/}}
}

@inproceedings{zangerle_ismir19,
title = {{Hit Song Prediction: Leveraging Low- and High-Level Audio Features}},
author = {Eva Zangerle and Ramona Huber and Michael V\"{o}tter and  Yi-Hsuan Yang},
year = {2019},
pages = {319--326},
booktitle = {{Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019)}},
url = {http://archives.ismir.net/ismir2019/paper/000037.pdf}
}

@inproceedings{bauer2019leveraging,
  title={Leveraging Multi-Method Evaluation for Multi-Stakeholder Settings},
  author={Bauer, Christine and Zangerle, Eva},
  year={2019},
  booktitle = {{Proceedings of the 1st Workshop on the Impact of Recommender Systems
co-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019)}},
  publisher = {ceur-ws.org},
}

@inproceedings{DBLP:conf/clef/DaelemansKMPPRS19,
author = {Walter Daelemans and
Mike Kestemont and
Enrique Manjavacas and
Martin Potthast and
Francisco M. Rangel Pardo and
Paolo Rosso and
G{\"{u}}nther Specht and
Efstathios Stamatatos and
Benno Stein and
Michael Tschuggnall and
Matti Wiegmann and
Eva Zangerle},
title = {Overview of {PAN} 2019: Bots and Gender Profiling, Celebrity Profiling,
Cross-Domain Authorship Attribution and Style Change Detection},
booktitle = {{Experimental {IR} Meets Multilinguality, Multimodality, and Interaction
- 10th International Conference of the {CLEF} Association, {CLEF}
2019, Lugano, Switzerland, September 9-12, 2019, Proceedings}},
pages = {402--416},
year = {2019},
doi = {10.1007/978-3-030-28577-7_30},
series = {Lecture Notes in Computer Science},
volume = {11696},
publisher = {Springer},
}

@InProceedings{zangerle:2019,
  author =              {Eva Zangerle and Michael Tschuggnall and G{\"{u}}nther Specht and Martin Potthast and Benno Stein},
  booktitle =           {{CLEF 2019 Labs and Workshops, Notebook Papers}},
  crossref =            {pan:2019},
  editor =              {Linda Cappellato and Nicola Ferro and {David {E.}} Losada and Henning M{\"{u}}ller},
  month =               sep,
  publisher =           {CEUR-WS.org},
  title =               {{Overview of the Style Change Detection Task at PAN 2019}},
  url =                 {http://ceur-ws.org/Vol-2380/},
  year =                {2019}
}

@inproceedings{DBLP:conf/wikis/SchmidtZ19,
author = {Manuel Schmidt and
Eva Zangerle},
title = {{Article Quality Classification on Wikipedia: Introducing Document
Embeddings and Content Features}},
booktitle = {{Proceedings of the 15th International Symposium on Open Collaboration,
OpenSym 2019, Sk{\"{o}}vde, Sweden, August 20-22, 2019}},
pages = {13:1--13:8},
year = {2019},
crossref = {DBLP:conf/wikis/2019},
url = {https://doi.org/10.1145/3306446.3340831},
doi = {10.1145/3306446.3340831},
publisher = {{ACM}},
year = {2019},
url = {https://dl.acm.org/citation.cfm?id=3306446},
isbn = {978-1-4503-6319-8},
}

@inproceedings{gvdb1019_1,
  author    = {Maximilian Mayerl and
               Michael V{\"{o}}tter and
               Eva Zangerle and
               G{\"{u}}nther Specht},
  title     = {Language Models for Next-Track Music Recommendation},
  booktitle = {Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg,
               Germany, June 11-14, 2019.},
  pages     = {15--19},
  year      = {2019},
  url       = {http://ceur-ws.org/Vol-2367/paper\_1.pdf},
}

@inproceedings{gvdb2019_2,
  author    = {Michael V{\"{o}}tter and
               Eva Zangerle and
               Maximilian Mayerl and
               G{\"{u}}nther Specht},
  title     = {Autoencoders for Next-Track-Recommendation},
  booktitle = {Proceedings of the 31st GI-Workshop Grundlagen von Datenbanken, Saarburg,
               Germany, June 11-14, 2019.},
  pages     = {20--25},
  year      = {2019},
  url       = {http://ceur-ws.org/Vol-2367/paper\_2.pdf},
}

@inproceedings{hiebelidentifikation,
title={{Zur Identifikation und Verortung von Bergnamen in alpiner Literatur}},
author={Hiebel, Gerald and Hanke, Klaus and Posch, Claudia and Rampl, Gerhard and Gruber, Elisabeth and Mussmann, Andrea and Zangerle, Eva},
booktitle = {{20. Internationale Geodätische Woche Obergurgl 2019}},
publisher = {{VDE Verlag}},
isbn = {978-3-87907-659-8},
pages = {91--100},
year = {2019},
url = {https://www.uibk.ac.at/geometrie-vermessung/gruppe_vermessung_und_geoinformation/geodaetische_wochen/obergurgl_2019/programm_072018.html}
}

@inproceedings{cmc18,
title = {Leiwand Oida: Geolocating Regional Linguistic Variation of German on Twitter},
author = {Bettina Larl and Eva Zangerle},
url = {https://www.uantwerpen.be/images/uantwerpen/container49896/files/proceedings_CMCcorpora2018.pdf},
year = {2018},
date = {2018-09-06},
booktitle = {Proceedings of the 6th Conference on Computer-Mediated Communication (CMC) and Social Media Corpora (CMC-corpora 2018)},
}

@inproceedings{8516495,
title = {Latent Feature Combination for Multi-Context Music Recommendation},
author = {Martin Pichl and Eva Zangerle},
doi = {10.1109/CBMI.2018.8516495},
year = {2018},
date = {2018-09-01},
booktitle = {2018 International Conference on Content-Based Multimedia Indexing (CBMI)},
pages = {1-6},
abstract = {In recent years, music aficionados have increasingly been consuming music via public music streaming platforms. Due to the size of the collections provided, music recommender systems have become a vital component as these aim to provide recommendations that match the user's current context as, throughout the day, users listen to music in numerous different contexts and situations. In this paper, we propose a multi-context-aware track recommender system that jointly exploits information about the current situation and musical preferences of users. To jointly model users by their situational and musical preferences, we cluster users based on their situational features and similarly, cluster music tracks based on their content features. Our experiments show that by relying on Factorization Machines for the computation of recommendations, the proposed approach allows to successfully leverage interaction effects between listening histories, situational and track content information, substantially outperforming a set of baseline recommenders.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@inproceedings{zangerle_ismir18,
title = {Content-based User Models: Modeling the Many Faces of Musical Preference},
author = {Eva Zangerle and Martin Pichl},
editor = {Emilia Gomez and Xiao Hu and Eric Humphrey and Emmanouil Benetos},
year = {2018},
date = {2018-09-22},
booktitle = {Proceedings of the 19th International Society for Music Information Retrieval Conference 2018 (ISMIR 2018)},
pages = {709--716}
}

@inproceedings{DBLP:conf/sigir/PichlPZ18,
  author    = {Martin Pichl and
               Bernward Pichl and
               Eva Zangerle},
  title     = {Carl: Sports Award Recommender},
  booktitle = {The {SIGIR} 2018 Workshop On eCommerce co-located with the 41st International
               {ACM} {SIGIR} Conference on Research and Development in Information
               Retrieval {(SIGIR} 2018), Ann Arbor, Michigan, USA, July 12, 2018.},
  year      = {2018},
  url       = {http://ceur-ws.org/Vol-2319/paper11.pdf},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2319},
  urn       = {urn:nbn:de:0074-2319-2},
  publisher = {CEUR-WS.org},
}

@inproceedings{smc18,
title = {#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems},
author = {Asmita Poddar and Eva Zangerle and Yi-Hsuan Yang },
doi = {10.5281/zenodo.1422565},
year = {2018},
booktitle = {Proceedings of the 15th Sound & Music Computing Conference},
address = {Limassol, Cyprus}
}

@inproceedings{Celik:2018:UIU:3213586.3226202,
 author = {Celik, Ilknur and Torre, Ilaria and Koceva, Frosina and Bauer, Christine and Zangerle, Eva and Knijnenburg, Bart},
 title = {UMAP 2018 Intelligent User-Adapted Interfaces: Design and Multi-Modal Evaluation (IUadaptMe) Workshop Chairs' Welcome and Organization},
 booktitle = {Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization},
 series = {UMAP '18},
 year = {2018},
 isbn = {978-1-4503-5784-5},
 location = {Singapore, Singapore},
 pages = {137--139},
 numpages = {3},
 url = {http://doi.acm.org/10.1145/3213586.3226202},
 doi = {10.1145/3213586.3226202},
 acmid = {3226202},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {cloud technologies, design, evaluation, intelligent context-aware user interface, intelligent user interfaces, mobile systems, multi-modal evaluation, personalized interaction, recommender systems, semantic technologies, social applications, user modelling, user-adapted systems, workshop},
}

@inproceedings{Zangerle:2018:CMR:3209219.3209258,
 author = {Zangerle, Eva and Pichl, Martin and Schedl, Markus},
 title = {Culture-Aware Music Recommendation},
 booktitle = {Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization},
 series = {UMAP '18},
 year = {2018},
 isbn = {978-1-4503-5589-6},
 location = {Singapore, Singapore},
 pages = {357--358},
 numpages = {2},
 url = {http://doi.acm.org/10.1145/3209219.3209258},
 doi = {10.1145/3209219.3209258},
 acmid = {3209258},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {music information retrieval, recommender systems, user modeling},
}