Publications

@article{kestemont2018overview,
  title={Overview of the author identification task at PAN-2018: cross-domain authorship attribution and style change detection},
  author={Kestemont, M and Tschuggnall, M and Stamatatos, E and Daelemans, W and Specht, G and Stein, B and Potthast, M},
  journal={Working Notes Papers of the CLEF},
  year={2018}
}

@article{murauer2018dynamic,
  title={Dynamic Parameter Search for Cross-Domain Authorship Attribution},
  author={Murauer, Benjamin and Tschuggnall, Michael and Specht, G{\"u}nther},
  journal={Working Notes of CLEF},
  year={2018}
}

@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{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: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},
} 

@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{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{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{Binna:2018:HHO:3183713.3196896,
 author = {Binna, Robert and Zangerle, Eva and Pichl, Martin and Specht, G\"{u}nther and Leis, Viktor},
 title = {HOT: A Height Optimized Trie Index for Main-Memory Database Systems},
 booktitle = {Proceedings of the 2018 International Conference on Management of Data},
 series = {SIGMOD '18},
 year = {2018},
 isbn = {978-1-4503-4703-7},
 location = {Houston, TX, USA},
 pages = {521--534},
 numpages = {14},
 url = {http://doi.acm.org/10.1145/3183713.3196896},
 doi = {10.1145/3183713.3196896},
 acmid = {3196896},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {height optimized trie, index, main memory, simd},
} 

@inproceedings{DBLP:conf/ecir/zangerle17,
title = {ALF-200k: Towards Extensive Multimodal Analyses of Music Tracks and Playlists},
author = {Eva Zangerle and Michael Tschuggnall and Stefan Wurzinger and Günther Specht},
doi = {10.1007/978-3-319-76941-7_48},
isbn = {978-3-319-76941-7},
year = {2018},
date = {2018-01-01},
booktitle = {Advances in Information Retrieval - 39th European Conference on IR Research, ECIR 2018},
pages = {584--590},
publisher = {Springer},
address = {Cham},
abstract = {In recent years, approaches in music information retrieval have been based on multimodal analyses of music incorporating audio as well as lyrics features. Because most of those approaches are lacking reusable, high-quality datasets, in this work we propose ALF-200k, a publicly available, novel dataset including 176 audio and lyrics features of more than 200,000 tracks and their attribution to more than 11,000 user-created playlists. While the dataset is of general purpose and thus, may be used in experiments for diverse music information retrieval problems, we present a first multimodal study on playlist features and particularly analyze, which type of features are shared within specific playlists and thus, characterize it. We show that while acoustic features act as the major glue between tracks contained in a playlists, also lyrics features are a powerful means to attribute tracks to playlists.}
}

@inproceedings{Murauer:2018:DMG:3184558.3191822,
 author = {Murauer, Benjamin and Specht, G\"{u}nther},
 title = {Detecting Music Genre Using Extreme Gradient Boosting},
 booktitle = {Companion of the The Web Conference 2018 on The Web Conference 2018},
 series = {WWW '18},
 year = {2018},
 isbn = {978-1-4503-5640-4},
 location = {Lyon, France},
 pages = {1923--1927},
 numpages = {5},
 url = {https://doi.org/10.1145/3184558.3191822},
 doi = {10.1145/3184558.3191822},
 acmid = {3191822},
 publisher = {International World Wide Web Conferences Steering Committee},
 address = {Republic and Canton of Geneva, Switzerland},
 keywords = {gradient boosting, music classification, neural network},
} 

@incollection{wikiworkshop18,
title = {Recommendation-Assisted Data Curation for Wikidata},
author = {Eva Zangerle and Claudia Müller-Birn},
doi = {10.5281/zenodo.1194790},
year = {2018},
date = {2018-04-24},
booktitle = {Wiki Workshop 2018 co-located with The Web Conference}
}

@inproceedings{milc2018,
title = {geMsearch: Personalized Explorative Music Search},
author = {Christian Esswein and Markus Schedl and Eva Zangerle},
url = {http://ceur-ws.org/Vol-2068/milc2.pdf},
year = {2018},
date = {2018-03-11},
booktitle = {Joint Proceedings of the ACM IUI 2018 Workshops co-located with the 23rd ACM Conference on Intelligent User Interfaces (ACM IUI 2018)},
publisher = {ceur-ws.org},
abstract = {Due to the rise of music streaming platforms, huge collections of music are now available to users on various devices. Within these collections, users aim to find and explore songs based on certain criteria reflecting their current and context-specific preferences. Currently, users are limited to either using search facilities or relying on recommender systems that suggest suitable tracks or artists. Using search facilities requires the user to have some idea about the targeted music and to formulate a query that accurately describes this music, whereas recommender systems are traditionally geared towards long-term shifts of user preferences in contrast to ad-hoc and interactive preference elicitation. To bridge this gap, we propose geMsearch, an approach for personalized, explorative music search based on graph embedding techniques. As the ecosystem of a music collection can be represented as a heterogeneous graph containing nodes describing e.g., tracks, artists, genres or users, we employ graph embedding techniques to learn low-dimensional vector representations for all nodes within the graph. This allows for efficient approximate querying of the collection and, more importantly, for employing visualization strategies that allow the user to explore the music collection in a 3D-space.}
}

@Article{Specht2018,
author="Specht, G{\"u}nther",
title="Die Forschungsgruppe Datenbanken und Informationssysteme an der Universit{\"a}t Innsbruck",
journal="Datenbank-Spektrum",
year="2018",
month="Mar",
day="01",
volume="18",
number="1",
pages="51--56",
abstract="In diesem Beitrag wird die Forschungsgruppe Datenbanken und Informationssysteme der Universit{\"a}t Innsbruck vorgestellt. Dabei wird ein {\"U}berblick {\"u}ber das Umfeld, die aktuellen Forschungsthemen und die Lehraktivit{\"a}ten gegeben.",
issn="1610-1995",
doi="10.1007/s13222-018-0278-9",
url="https://doi.org/10.1007/s13222-018-0278-9"
}

@inproceedings{Murauer2018Translation,
  title={{On the Influence of Machine Translation on Language Origin Obfuscation}},
  author={Murauer, Benjamin and Tschuggnall, Michael and Specht, G\"unther},
  year={2018},
  location={Hanoi, Vietnam},
  booktitle={Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing'2018)},
  month=3,

}

@PHDTHESIS {pichl2018-diss,
    author = {Martin Pichl},
    title  = {{Multi-Context-Aware Recommender Systems: A Study on Music Recommendation}},
    school = {University of Innsbruck, Department of Computer Science},
    year   = {2018},
    month  = {feb}
}

@article{freebim2017,
  author={Specht, G{\"u}nther and Breuss, Rainer},
  title={{Der freeBIM Merkmalserver}},
  booktitle={Beton-Kalender},
  pages={363--366},
  volume={1},
  url={https://www.ernst-und-sohn.de/beton-kalender-2018},
  year={2018},
}

@inproceedings{bauerinformation,
  title={Information Imbalance and Responsibility in Recommender Systems},
  author={Bauer, Christine and Zangerle, Eva},
  booktitle = {Workshop Proceeding of the 2nd Workshop on Green (Responsible, Ethical and Social) IT and IS ? the Corporate Perspective (GRES-IT/IS)},
  type = {Working Papers on Information Systems, Information Business and Operations},
  year = {2018},
  organization = {Department f{\"u}r Informationsverarbeitung und Prozessmanagement, WU Vienna University of Economics and Business},
  url = {https://epub.wu.ac.at/7681/},
}

@online{dha17_semohi,
title = {Semantics for Mountaineering History},
author = {Gerald Hiebel and Claudia Posch and Gerhard Rampl and Elisabeth Gruber and Klaus Hanke and Eva Zangerle},
url = {https://www.uibk.ac.at/congress/dha2017/bilder-und-dateien/semantics-for-mountaineering-history.pdf},
year = {2017},
month = {12},
date = {2017-12-06},
organization = {4th Digital Humanities Austria Conference},
howpublished = {4th Digital Humanities Austria Conference },
keywords = {},
tppubtype = {online}
}

@inproceedings{sympmm,
title = {Mining Culture-Specific Music Listening Behavior from Social Media Data},
author = {Pichl, Martin and Zangerle, Eva and Specht, G\"unther and Markus Schedl},
doi = {10.1109/ISM.2017.35},
isbn = {978-1-5386-2937-6/17},
year = {2017},
booktitle = {IEEE International Symposium on Multimedia, ISM 2017, Taichung, Taiwan, December 11-13, 2017},
pages = {208--215},
publisher = {IEEE Computer Society}
}

@online{dha17_lyrics,
title = {Analyzing Coherent Characteristics in Music Playlists},
author = {Eva Zangerle and Michael Tschuggnall and Stefan Wurzinger and G\"{u}nther Specht},
year = {2017},
date = {2017-12-06},
organization = {4th Digital Humanities Austria Conference},
howpublished = {4th Digital Humanities Austria Conference},
url = {https://www.uibk.ac.at/congress/dha2017/bilder-und-dateien/poster_zangerle.pdf}
}

@online{dha17_archive,
title = {Visualization Strategies for Digital Archives. The Case of the Ernst-von-Glasersfeld-Archive},
author = {Barbara Laner and Andy Stauder and Eva Zangerle and Theo Hug},
year = {2017},
date = {2017-12-06},
journal = {4th Digital Humanities Austria Conference },
organization = {4th Digital Humanities Austria Conference},
keywords = {},
pubstate = {published},
tppubtype = {online}
}

@inproceedings{Silbernagl:2017:ROT:3148150.3148159,
 author = {Silbernagl, Doris and Krismer, Nikolaus and Augsten, Nikolaus and Specht, G\"{u}nther},
 title = {Recommending OSM Tags To Improve Metadata Quality},
 booktitle = {Proceedings of the 1st ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks},
 series = {LocalRec'17},
 year = {2017},
 isbn = {978-1-4503-5499-8},
 location = {Redondo Beach, CA, USA},
 pages = {6:1--6:10},
 articleno = {6},
 numpages = {10},
 url = {http://doi.acm.org/10.1145/3148150.3148159},
 doi = {10.1145/3148150.3148159},
 acmid = {3148159},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {OpenStreetMap, Recommendation, Set Similarity, Top-k Retrieval},
} 

@PHDTHESIS {silbernagl2017-diss,
    author = {Doris Silbernagl},
    title  = {{Quality analyses and improvement in geographical information systems in the special case of OpenStreetMap}},
    school = {University of Innsbruck, Department of Computer Science},
    year   = {2017},
    month  = {nov}
}

@PHDTHESIS {krismer2017-diss,
    author = {Nikolaus Krismer},
    title  = {{Enhancing Isochrones in Multimodal Spatial Networks}},
    school = {University of Innsbruck, Department of Computer Science},
    year   = {2017},
    month  = {nov}
}