

Günther Specht, Johannes Kessler, Maximilian Mayerl and Michael Tschuggnall: RelaX - Interaktive Relationale Algebra in der Lehre. In Datenbank-Spektrum. (1) 2021
@Article{Specht2021ReLaX, author={Specht, G{\"u}nther and Kessler, Johannes and Mayerl, Maximilian and Tschuggnall, Michael}, title={RelaX - Interaktive Relationale Algebra in der Lehre}, journal={Datenbank-Spektrum}, year={2021}, month={Jan}, day={24}, abstract={Das relationale Modell und insbesondere die relationale Algebra bilden die Grundlage jedes relationalen Datenbanksystems. Daher ist es in der Lehre wichtig, den Studierenden eine fundierte Einf{\"u}hrung in die relationale Algebra zu geben. Nur so erhalten sie ein vertieftes Verst{\"a}ndnis f{\"u}r die interne Ausf{\"u}hrung einer Anfrage. W{\"a}hrend es viele M{\"o}glichkeiten gibt, SQL zu {\"u}ben, fehlen bisher gr{\"o}{\ss}tenteils solche M{\"o}glichkeiten f{\"u}r die relationale Algebra. Sie wird meist nur theoretisch unterrichtet. Darum hat die Forschungsgruppe DBIS an der Universit{\"a}t Innsbruck ein rein webbasiertes Tool entwickelt, das die Lehre der relationalen Algebra erleichtern und verbessern soll: RelaX. RelaX ist unter http://dbis-uibk.github.io/relax/frei verf{\"u}gbar.}, issn={1610-1995}, doi={10.1007/s13222-021-00367-x}, url={https://doi.org/10.1007/s13222-021-00367-x} }
Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Martin Potthast, Francisco Rangel, Paolo Rosso, Günther Specht, Efstathios Stamatatos, Benno Stein, Matti Wiegmann and Eva Zangerle: Shared Tasks on Authorship Analysis at PAN 2020. In Advances in Information Retrieval (ECIR 2020), pages 508-516. Springer International Publishing, 2020
@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, ECIR 2020}, 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} }
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 (to be published)
@inproceedings{mediaeval2020, author = {Michael Vötter and Maximilian Mayerl and Günther Specht and Eva Zangerle}, booktitle = {Working Notes Proceedings of the MediaEval 2020 Workshop}, month = {12}, publisher = {ceur-ws.org}, title = {Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups}, year = {2020} }
Manfred Moosleitner, Benjamin Murauer and Günther Specht: Detecting Conspiracy Tweets using Support Vector Machines. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020 (to be published).
@inproceedings{mediaeval2020conspiracy, author = {Moosleitner, Manfred and Murauer, Benjamin and Specht, Günther}, booktitle = {Working Notes Proceedings of the MediaEval 2020 Workshop}, month = {12}, publisher = {ceur-ws.org}, title = {Detecting Conspiracy Tweets using Support Vector Machines}, year = {2020} }
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
@inproceedings{zangerle2020overview, title={Overview of the style change detection task at PAN 2020}, author={Zangerle, Eva and Mayerl, Maximilian and Specht, G{\"u}nther and Potthast, Martin and Stein, Benno}, year={2020}, organization={CLEF} }
Michael Tschuggnall, Benjamin Murauer and Günther Specht: Reduce & Attribute: Two-Step Authorship Attribution for Large-Scale Problems. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 951-960. Association for Computational Linguistics, 2019
@inproceedings{tschuggnall-etal-2019-reduce, title = "Reduce {\textbackslash}{\&} Attribute: Two-Step Authorship Attribution for Large-Scale Problems", author = {Tschuggnall, Michael and Murauer, Benjamin and Specht, G{\"u}nther}, booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/K19-1089", doi = "10.18653/v1/K19-1089", pages = "951--960", }
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
@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} }
S Coassin, S Schönherr, H Weissensteiner, G Erhart, S Di Maio, L Forer, C Lamina, A Peters, B Thorand, KU Eckardt and others: A Comprehensive Map Of The Variability In The Lipoprotein (A) Kiv 2 Repeat Region And Follow-Up Of The Kiv-2 Arg20ter Mutation In 11,000 Individuals. In Atherosclerosis, vol. 287, pages e58. Elsevier, 2019
@article{coassin2019comprehensive, title={A Comprehensive Map Of The Variability In The Lipoprotein (A) Kiv 2 Repeat Region And Follow-Up Of The Kiv-2 Arg20ter Mutation In 11,000 Individuals}, author={Coassin, S and Sch{\"o}nherr, S and Weissensteiner, H and Erhart, G and Di Maio, S and Forer, L and Lamina, C and Peters, A and Thorand, B and Eckardt, KU and others}, journal={Atherosclerosis}, volume={287}, pages={e58}, year={2019}, publisher={Elsevier}, doi = {10.1016/j.atherosclerosis.2019.06.164} }
Benjamin Murauer and Günther Specht: Generating Cross-Domain Text Classification Corpora from Social Media Comments. In Experimental IR Meets Multilinguality, Multimodality, and Interaction, pages 114-125. Springer International Publishing, 2019
@InProceedings{10.1007/978-3-030-28577-7_7, author="Murauer, Benjamin and Specht, G{\"u}nther", editor="Crestani, Fabio and Braschler, Martin and Savoy, Jacques and Rauber, Andreas and M{\"u}ller, Henning and Losada, David E. and Heinatz B{\"u}rki, Gundula and Cappellato, Linda and Ferro, Nicola", title="Generating Cross-Domain Text Classification Corpora from Social Media Comments", booktitle="Experimental IR Meets Multilinguality, Multimodality, and Interaction", year="2019", publisher="Springer International Publishing", address="Cham", pages="114--125", isbn="978-3-030-28577-7" }
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
@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}, }
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
@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}, }
Michael Tschuggnall, Thibault Gerrier and Günther Specht: StyleExplorer: A Toolkit for Textual Writing Style Visualization. In Proceedings of the 41th European Conference on Information Retrieval (ECIR 2019): Advances in Information Retrieval, pages 220-224. Springer International Publishing, 2019
@InProceedings{10.1007/978-3-030-15719-7_28, author="Tschuggnall, Michael and Gerrier, Thibault and Specht, G{\"u}nther", editor="Azzopardi, Leif and Stein, Benno and Fuhr, Norbert and Mayr, Philipp and Hauff, Claudia and Hiemstra, Djoerd", title="StyleExplorer: A Toolkit for Textual Writing Style Visualization", booktitle="Proceedings of the 41th European Conference on Information Retrieval (ECIR 2019): Advances in Information Retrieval", year="2019", publisher="Springer International Publishing", address="Cham", pages="220--224", isbn="978-3-030-15719-7" }
Georg Fröch, Werner Gächter, Arnold Tautschnig and Günther Specht: Merkmalserver im Open-BIM-Prozess. In Bautechnik. 2019
@article{doi:10.1002/bate.201800092, author = {Fröch, Georg and Gächter, Werner and Tautschnig, Arnold and Specht, Günther}, title = {Merkmalserver im Open-BIM-Prozess}, journal = {Bautechnik}, doi = {10.1002/bate.201800092}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/bate.201800092}, eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/bate.201800092}, year= {2019} }
Johannes Kessler, Michael Tschuggnall and Günther Specht. RelaX: A Webbased Execution and Learning Tool for Relational Algebra. In Proceedings of the 18th Fachtagung des GI-Fachbereichs Datenbanksysteme für Business, Technologie und Web (BTW), March 2019, Rostock, LNI, pages 503-506, 2019
@inproceedings{kessler2019relax, Address = {Rostock, Germany}, Author = {Johannes Kessler, Michael Tschuggnall and G{\"u}nther Specht}, Booktitle = {Proceedings of the 18th Fachtagung des GI-Fachbereichs Datenbanksysteme f{\"u}r Business, Technologie und Web (BTW)}, Date-Added = {2019-03-26 13:34:11 +0100}, Date-Modified = {2019-03-26 13:36:35 +0100}, Month = {March}, Pages = {503-506}, Publisher = {GI}, Series = {LNI}, Title = {{RelaX: A Webbased Execution and Learning Tool for Relational Algebra}}, Year = {2019}}
Stefan Coassin, Sebastian Schönherr, Hansi Weissensteiner, Gertraud Erhart, Lukas Forer, Jamie Lee Losso, Claudia Lamina, Margot Haun, Gerd Utermann, Bernhard Paulweber, Günther Specht and Florian Kronenberg: A comprehensive map of single-base polymorphisms in the hypervariable LPA kringle IV type 2 copy number variation region. In Journal of Lipid Research, vol. 60, no. 1, pages 186-199. 2019
@article{Coassin01012019, author = {Coassin, Stefan and Schönherr, Sebastian and Weissensteiner, Hansi and Erhart, Gertraud and Forer, Lukas and Losso, Jamie Lee and Lamina, Claudia and Haun, Margot and Utermann, Gerd and Paulweber, Bernhard and Specht, Günther and Kronenberg, Florian}, title = {A comprehensive map of single-base polymorphisms in the hypervariable LPA kringle IV type 2 copy number variation region}, volume = {60}, number = {1}, pages = {186-199}, year = {2019}, doi = {10.1194/jlr.M090381}, URL = {http://www.jlr.org/content/60/1/186.abstract}, eprint = {http://www.jlr.org/content/60/1/186.full.pdf+html}, journal = {Journal of Lipid Research} }
Benjamin Murauer, Michael Tschuggnall and Günther Specht: Dynamic Parameter Search for Cross-Domain Authorship Attribution. In Working Notes of CLEF. 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} }
M Kestemont, M Tschuggnall, E Stamatatos, W Daelemans, G Specht, B Stein and M Potthast: Overview of the author identification task at PAN-2018: cross-domain authorship attribution and style change detection. In Working Notes Papers of the CLEF. 2018
@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} }
Robert Binna, Eva Zangerle, Martin Pichl, Günther Specht and Viktor Leis: HOT: A Height Optimized Trie Index for Main-Memory Database Systems. In Proceedings of the 2018 International Conference on Management of Data (SIGMOD 2018), pages 521-534. ACM, 2018
@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}, }
Benjamin Murauer and Günther Specht: Detecting Music Genre Using Extreme Gradient Boosting. In Companion of the The Web Conference 2018 on The Web Conference 2018, pages 1923-1927. International World Wide Web Conferences Steering Committee, 2018.
@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}, }
Eva Zangerle, Michael Tschuggnall, Stefan Wurzinger and Günther Specht: ALF-200k: Towards Extensive Multimodal Analyses of Music Tracks and Playlists. In Advances in Information Retrieval - 39th European Conference on IR Research (ECIR 2018), pages 584-590. Springer, 2018
@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.} }