

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} }
Maximilian Mayerl, Michael Vötter, 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 = {Maximilian Mayerl and Michael Vötter 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} }
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} }
Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso and others: Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection. In International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2020), pages 372-383. 2020.
@inproceedings{bevendorff2020overview, title={Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection}, author={Bevendorff, Janek and Ghanem, Bilal and Giachanou, Anastasia and Kestemont, Mike and Manjavacas, Enrique and Markov, Ilia and Mayerl, Maximilian and Potthast, Martin and Rangel, Francisco and Rosso, Paolo and others}, booktitle={International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2020)}, pages={372--383}, year={2020}, organization={Springer} }
Maximilian Mayerl, Michael Vötter, Manfred Moosleitner and Eva Zangerle: Comparing Lyrics Features for Genre Recognition. In Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), pages 73-77. 2020.
@inproceedings{mayerl2020comparing, title={Comparing Lyrics Features for Genre Recognition}, author={Mayerl, Maximilian and V{\"o}tter, Michael and Moosleitner, Manfred and Zangerle, Eva}, booktitle={Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA)}, pages={73--77}, year={2020} }
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}, }
Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Boyu Chen, Yi-Hsuan Yang and Eva Zangerle: Recognizing Song Mood and Theme Using Convolutional Recurrent Neural Networks. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.
@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 = {2019} }
Hsiao-Tzu Hung, Yu-Hua Chen, Maximilian Mayerl, Michael Vötter, Eva Zangerle and Yi-Hsuan Yang: MediaEval 2019 Emotion and Theme Recognition task: A VQ-VAE Based Approach. In Working Notes Proceedings of the MediaEval 2019 Workshop. ceur-ws.org, 2019.
@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} }
Benjamin Murauer, Maximilian Mayerl, Michael Tschuggnall, Eva Zangerle, Martin Pichl and Günther Specht: Hierarchical Multilabel Classification and Voting for Genre Classification. In CEURS Working Notes Proceedings of the MediaEval 2017 Workshop. CEUR-WS.org, 2017
@article{Murauer2017Genre, title={Hierarchical Multilabel Classification and Voting for Genre Classification}, author={Murauer, Benjamin and Mayerl, Maximilian and Tschuggnall, Michael and Zangerle, Eva and Pichl, Martin and Specht, G{\"u}nther}, booktitle={CEURS Working Notes Proceedings of the MediaEval 2017 Workshop}, publisher={CEUR-WS.org}, city={Dublin, Ireland}, year={2017}, url={http://ceur-ws.org/Vol-1984/Mediaeval_2017_paper_41.pdf}, }