Ass.-Prof. Dr. Eva Zangerle

@inproceedings{zangerle-recsys-2022,
author = {Zangerle, Eva and Bauer, Christine and Said, Alan},
title = {Second Workshop: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2022)},
year = {2022},
isbn = {9781450392785},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3523227.3547408},
doi = {10.1145/3523227.3547408},
booktitle = {Proceedings of the 16th ACM Conference on Recommender Systems},
pages = {652–653},
numpages = {2},
keywords = {evaluation, recommender systems, personalized systems, methods, information retrieval},
location = {Seattle, WA, USA},
series = {RecSys '22}
}

@inproceedings{DBLP:conf/clef/BevendorffCFHKK22,
  author    = {Janek Bevendorff and
               Berta Chulvi and
               Elisabetta Fersini and
               Annina Heini and
               Mike Kestemont and
               Krzysztof Kredens and
               Maximilian Mayerl and
               Reynier Ortega{-}Bueno and
               Piotr Pezik and
               Martin Potthast and
               Francisco Rangel and
               Paolo Rosso and
               Efstathios Stamatatos and
               Benno Stein and
               Matti Wiegmann and
               Magdalena Wolska and
               Eva Zangerle},
  title     = {Overview of {PAN} 2022: Authorship Verification, Profiling Irony and
               Stereotype Spreaders, and Style Change Detection},
  booktitle = {Experimental {IR} Meets Multilinguality, Multimodality, and Interaction
               - 13th International Conference of the {CLEF} Association, {CLEF}
               2022, Bologna, Italy, September 5-8, 2022, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {13390},
  pages     = {382--394},
  publisher = {Springer},
  year      = {2022},
  url       = {https://doi.org/10.1007/978-3-031-13643-6\_24},
  doi       = {10.1007/978-3-031-13643-6\_24},
}

@inproceedings{DBLP:conf/clef/ZangerleMP022,
  author    = {Eva Zangerle and
               Maximilian Mayerl and
               Martin Potthast and
               Benno Stein},
  editor    = {Guglielmo Faggioli and
               Nicola Ferro and
               Allan Hanbury and
               Martin Potthast},
  title     = {Overview of the Style Change Detection Task at {PAN} 2022},
  booktitle = {Proceedings of the Working Notes of {CLEF} 2022 - Conference and Labs
               of the Evaluation Forum, Bologna, Italy, September 5th - to - 8th,
               2022},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {3180},
  pages     = {2344--2356},
  publisher = {CEUR-WS.org},
  year      = {2022},
  url       = {http://ceur-ws.org/Vol-3180/paper-186.pdf},
  timestamp = {Wed, 10 Aug 2022 16:26:45 +0200},
  biburl    = {https://dblp.org/rec/conf/clef/ZangerleMP022.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{10.1145/3556536,
author = {Zangerle, Eva and Bauer, Christine},
title = {Evaluating Recommender Systems: Survey and Framework},
year = {2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
issn = {0360-0300},
url = {https://doi.org/10.1145/3556536},
doi = {10.1145/3556536},
abstract = {The comprehensive evaluation of the performance of a recommender system is a complex endeavor: many facets need to be considered in configuring an adequate and effective evaluation setting. Such facets include, for instance, defining the specific goals of the evaluation, choosing an evaluation method, underlying data, and suitable evaluation metrics. In this paper, we consolidate and systematically organize this dispersed knowledge on recommender systems evaluation. We introduce the “Framework for EValuating Recommender systems” (FEVR) that we derive from the discourse on recommender systems evaluation. In FEVR, we categorize the evaluation space of recommender systems evaluation. We postulate that the comprehensive evaluation of a recommender system frequently requires considering multiple facets and perspectives in the evaluation. The FEVR framework provides a structured foundation to adopt adequate evaluation configurations that encompass this required multi-facettedness and provides the basis to advance in the field. We outline and discuss the challenges of a comprehensive evaluation of recommender systems, and provide an outlook on what we need to embrace and do to move forward as a research community.},
note = {Just Accepted},
journal = {ACM Comput. Surv.},
month = {jul},
keywords = {Framework for EValuating Recommender systems, survey, FEVR}
}

@InProceedings{10.1007/978-3-030-99739-7_42,
author="Bevendorff, Janek
and Chulvi, Berta
and Fersini, Elisabetta
and Heini, Annina
and Kestemont, Mike
and Kredens, Krzysztof
and Mayerl, Maximilian
and Ortega-Bueno, Reyner
and Pezik, Piotr
and Potthast, Martin
and Rangel, Francisco
and Rosso, Paolo
and Stamatatos, Efstathios
and Stein, Benno
and Wiegmann, Matti
and Wolska, Magdalena
and Zangerle, Eva",
editor="Hagen, Matthias
and Verberne, Suzan
and Macdonald, Craig
and Seifert, Christin
and Balog, Krisztian
and N{\o}rv{\aa}g, Kjetil
and Setty, Vinay",
title="Overview of PAN 2022: Authorship Verification, Profiling Irony and Stereotype Spreaders, Style Change Detection, and Trigger Detection",
booktitle="Advances in Information Retrieval. ECIR 2022",
year="2022",
publisher="Springer International Publishing",
address="Cham",
pages="331--338",
abstract="The paper gives a brief overview of the four shared tasks to be organized at the PAN 2022 lab on digital text forensics and stylometry hosted at the CLEF 2022 conference. The tasks include authorship verification across discourse types, multi-author writing style analysis, author profiling, and content profiling. Some of the tasks continue and advance past editions (authorship verification and multi-author analysis) and some are new (profiling irony and stereotypes spreaders and trigger detection). The general goal of the PAN shared tasks is to advance the state of the art in text forensics and stylometry while ensuring objective evaluation on newly developed benchmark datasets.",
isbn="978-3-030-99739-7", 
doi="10.1007/978-3-030-99739-7_42",
url="https://link.springer.com/chapter/10.1007/978-3-030-99739-7_42"
}

@article{10.1145/3506692,
author = {Binna, Robert and Zangerle, Eva and Pichl, Martin and Specht, G\"{u}nther and Leis, Viktor},
title = {Height Optimized Tries},
year = {2022},
issue_date = {March 2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {47},
number = {1},
issn = {0362-5915},
url = {https://doi.org/10.1145/3506692},
doi = {10.1145/3506692},
abstract = {We present the Height Optimized Trie (HOT), a fast and space-efficient in-memory index structure. The core algorithmic idea of HOT is to dynamically vary the number of bits considered at each node, which enables a consistently high fanout and thereby good cache efficiency. For a fixed maximum node fanout, the overall tree height is minimal and its structure is deterministically defined. Multiple carefully engineered node implementations using SIMD instructions or lightweight compression schemes provide compactness and fast search and optimize HOT structures for different usage scenarios. Our experiments, which use a wide variety of workloads and data sets, show that HOT outperforms other state-of-the-art index structures for string keys both in terms of search performance and memory footprint, while being competitive for integer keys.},
journal = {ACM Trans. Database Syst.},
month = {apr},
articleno = {3},
numpages = {46},
keywords = {main memory, SIMD, Height optimized trie, index structure}
}

@article{zangerle:sigirforum:2021,
author = {Zangerle, Eva and Bauer, Christine and Said, Alan},
title = {Report on the 1st Workshop on the Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES 2021) at RecSys 2021},
year = {2022},
issue_date = {December 2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {55},
number = {2},
issn = {0163-5840},
url = {https://doi.org/10.1145/3527546.3527565},
doi = {10.1145/3527546.3527565},
abstract = {Evaluation is a central step when it comes to developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2021 workshop at the 15th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current state of evaluation from different, and maybe even diverging or contradictory perspectives.Date: 25 and 30 September 2021.Website: https://perspectives-ws.github.io/2021/.},
journal = {SIGIR Forum},
month = {mar},
articleno = {16},
numpages = {5}
}

@InProceedings{moosleitner2022corattingattacks,
  author    = {Moosleitner, Manfred and Specht, G\"{u}nther and Zangerle, Eva},
  booktitle = {Proceedings of the 32nd GI-Workshop Grundlagen von Datenbanksysteme (GvDB'21) },
  title     = {{Co-rating Attacks on Recommendation Algorithms}},
  year      = {2022},
}

@inproceedings{mayerlRecognizingSongMood2021,
	title = {Recognizing Song Mood and Theme: Clustering-based Ensembles},
	booktitle = {Working Notes Proceedings of the MediaEval 2021 Workshop},
	publisher = {ceur-ws.org},
	author = {Mayerl, Maximilian and Vötter, Michael and Peintner, Andreas and Specht, Günther and Zangerle, Eva},
	month = {12},
	year = {2021},
}

@inproceedings{voetter:ism:2021,
  author    = {
               Michael V\"{o}tter and Maximilian Mayerl and G\"{u}nther Specht and Eva Zangerle},
  title     = {Novel Datasets for Evaluating Song Popularity Prediction Tasks},
  booktitle = {{IEEE} International Symposium on Multimedia, {ISM} 2021, Virtual Event, November 29 -- December 1, 2021},
  pages     = {166--173},
  publisher = {{IEEE}},
  year      = {2021},
  doi       = {10.1109/ISM52913.2021.00034},
}

@proceedings{zangerle:perspectives:2021,
  editor    = {Eva Zangerle and 
               Christine Bauer and 
              Alan Said},
  title     = {Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021
co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021)},
  series    = {{CEUR} Workshop Proceedings},
  volume    = {2955},
  publisher = {CEUR-WS.org},
  year      = {2021},
  url       = {http://ceur-ws.org/Vol-2955},
  urn       = {urn:nbn:de:0074-2955-1},
}

@InProceedings{zangerle:2020,
  author =              {Eva Zangerle and Maximilian Mayerl and Martin Potthast and Benno Stein},
  booktitle =           {{CLEF 2021 Labs and Workshops, Notebook Papers}},
  editor =              {Guglielmo Faggioli and Nicola Ferro and Alexis Joly and Maria Maistro and Florina Piroi},
  publisher =           {CEUR-WS.org},
  title =               {{Overview of the Style Change Detection Task at PAN 2021}},
  url =                 {http://ceur-ws.org/Vol-2936/},
  year =                2021,
  pages = {1760--1771}
}

@inproceedings{DBLP:conf/clef/BevendorffCSKMM21,
  author    = {Janek Bevendorff and
               Berta Chulvi and
               Gretel Liz De la Pe{\~{n}}a Sarrac{\'{e}}n and
               Mike Kestemont and
               Enrique Manjavacas and
               Ilia Markov and
               Maximilian Mayerl and
               Martin Potthast and
               Francisco Rangel and
               Paolo Rosso and
               Efstathios Stamatatos and
               Benno Stein and
               Matti Wiegmann and
               Magdalena Wolska and
               Eva Zangerle},
  editor    = {K. Sel{\c{c}}uk Candan and
               Bogdan Ionescu and
               Lorraine Goeuriot and
               Birger Larsen and
               Henning M{\"{u}}ller and
               Alexis Joly and
               Maria Maistro and
               Florina Piroi and
               Guglielmo Faggioli and
               Nicola Ferro},
  title     = {Overview of {PAN} 2021: Authorship Verification, Profiling Hate Speech
               Spreaders on Twitter, and Style Change Detection},
  booktitle = {Experimental {IR} Meets Multilinguality, Multimodality, and Interaction
               - 12th International Conference of the {CLEF} Association, {CLEF}
               2021, Virtual Event, September 21-24, 2021, Proceedings},
  series    = {Lecture Notes in Computer Science},
  volume    = {12880},
  pages     = {419--431},
  publisher = {Springer},
  year      = {2021},
  url       = {https://doi.org/10.1007/978-3-030-85251-1\_26},
  doi       = {10.1007/978-3-030-85251-1\_26},
}

@inproceedings{10.1145/3460231.3470929,
author = {Zangerle, Eva and Bauer, Christine and Said, Alan},
title = {Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES)},
year = {2021},
isbn = {9781450384582},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3460231.3470929},
doi = {10.1145/3460231.3470929},
booktitle = {Fifteenth ACM Conference on Recommender Systems},
pages = {794–795},
numpages = {2},
keywords = {recommender systems, evaluation, methods},
location = {Amsterdam, Netherlands},
series = {RecSys '21}
}

@article{pichl2020user,
  title={User models for multi-context-aware music recommendation},
  author={Pichl, Martin and Zangerle, Eva},
  journal={Multimedia Tools and Applications},
  pages={22509--22531},
  year={2021},
  publisher={Springer},
  doi={10.1007/s11042-020-09890-7},
  volume=80,
  number={15}
}

@InProceedings{10.1007/978-3-030-72240-1_66,
author="Bevendorff, Janek
and Chulvi, BERTa
and Sarrac{\'e}n, Gretel Liz De La Pe{\~{n}}a
and Kestemont, Mike
and Manjavacas, Enrique
and Markov, Ilia
and Mayerl, Maximilian
and Potthast, Martin
and Rangel, Francisco
and Rosso, Paolo
and Stamatatos, Efstathios
and Stein, Benno
and Wiegmann, Matti
and Wolska, Magdalena
and Zangerle, Eva",
editor="Hiemstra, Djoerd
and Moens, Marie-Francine
and Mothe, Josiane
and Perego, Raffaele
and Potthast, Martin
and Sebastiani, Fabrizio",
title="Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection",
booktitle="Advances in  Information Retrieval. ECIR 2021",
year="2021",
publisher="Springer International Publishing",
address="Cham",
pages="567--573",
abstract="The paper gives a brief overview of the three shared tasks to be organized at the PAN 2021 lab on digital text forensics and stylometry hosted at the CLEF conference. The tasks include authorship verification across domains, author profiling for hate speech spreaders, and style change detection for multi-author documents. In part the tasks are new and in part they continue and advance past shared tasks, with the overall goal of advancing the state of the art, providing for an objective evaluation on newly developed benchmark datasets.",
isbn="978-3-030-72240-1"
}

@ARTICLE{8382228,
  author={Eva {Zangerle} and Chih-Ming {Chen} and Ming-Feng {Tsai} and Yi-Hsuan {Yang}},
  journal={IEEE Transactions on Affective Computing}, 
  title={Leveraging Affective Hashtags for Ranking Music Recommendations}, 
  year={2021},
  volume={12},
  number={1},
  pages={78-91},
  doi={10.1109/TAFFC.2018.2846596}}

@article{kowald2021support,
  title={Support the underground: characteristics of beyond-mainstream music listeners},
  author={Kowald, Dominik and Muellner, Peter and Zangerle, Eva and Bauer, Christine and Schedl, Markus and Lex, Elisabeth},
  journal={EPJ Data Science},
  volume={10},
  number={1},
  pages={1--26},
  year={2021},
  publisher={Springer}
}

@proceedings{DBLP:conf/ismir/2020,
  author    = {Julie Cumming and
               Jin Ha Lee and
               Brian McFee and
               Markus Schedl and
               Johanna Devaney and
               Cory McKay and
               Eva Zangerle and
               Timothy de Reuse},
  title     = {Proceedings of the 21th International Society for Music Information
               Retrieval Conference, {ISMIR} 2020, Montreal, Canada, October 11-16,
               2020},
  year      = {2020},
  isbn      = {978-0-9813537-1-5},
  timestamp = {Mon, 19 Jul 2021 15:30:03 +0200},
  biburl    = {https://dblp.org/rec/conf/ismir/2020.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{bevendorff:clef:2020,
 author = {Janek Bevendorff and Bilal Ghanem and Anastasia Giachanou and Mike Kestemont and Enrique Manjavacas and Ilia Markov and Maximilian Mayerl and Martin Potthast and Francisco Rangel and Paolo Rosso and Günther Specht and Efstathios Stamatatos and Benno~Stein and Matti Wiegmann and Eva Zangerle},
 booktitle = {11th International Conference of the CLEF Association (CLEF 2020)},
 editor = {Avi Arampatzis and Evangelos Kanoulas and Theodora Tsikrika and Stefanos Vrochidis and Hideo
Joho and Christina Lioma and Carsten Eickhoff and Aurélie Névéol and Linda Cappellato and Nicola Ferro},
 month = {September},
 publisher = {Springer},
 title = {Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection},
 url = {http://ceur-ws.org/Vol-2696/},
 venue = {Thessaloniki, Greece},
 year = {2020}
}