Mevlüt Bagci

PhD Student

Goethe-Universität Frankfurt am Main
Robert-Mayer-Straße 10
Room 401d
D-60325 Frankfurt am Main
D-60054 Frankfurt am Main (use for package delivery)
Postfach / P.O. Box: 154
Phone:
Mail:

Office Hour: Tuesday, 8-10 AM

Teaching

  • Practical: Multilingual systems with AI 

Publications

2024

Giuseppe Abrami, Mevlüt Bagci and Alexander Mehler. 2024. German Parliamentary Corpus (GerParCor) Reloaded. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 7707–7716.
BibTeX
@inproceedings{Abrami:et:al:2024:a,
  abstract  = {In 2022, the largest German-speaking corpus of parliamentary protocols
               from three different centuries, on a national and federal level
               from the countries of Germany, Austria, Switzerland and Liechtenstein,
               was collected and published - GerParCor. Through GerParCor, it
               became possible to provide for the first time various parliamentary
               protocols which were not available digitally and, moreover, could
               not be retrieved and processed in a uniform manner. Furthermore,
               GerParCor was additionally preprocessed using NLP methods and
               made available in XMI format. In this paper, GerParCor is significantly
               updated by including all new parliamentary protocols in the corpus,
               as well as adding and preprocessing further parliamentary protocols
               previously not covered, so that a period up to 1797 is now covered.
               Besides the integration of a new, state-of-the-art and appropriate
               NLP preprocessing for the handling of large text corpora, this
               update also provides an overview of the further reuse of GerParCor
               by presenting various provisioning capabilities such as API's,
               among others.},
  address   = {Torino, Italy},
  author    = {Abrami, Giuseppe and Bagci, Mevl{\"u}t and Mehler, Alexander},
  booktitle = {Proceedings of the 2024 Joint International Conference on Computational
               Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
  editor    = {Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro
               and Sakti, Sakriani and Xue, Nianwen},
  pages     = {7707--7716},
  publisher = {ELRA and ICCL},
  title     = {{G}erman Parliamentary Corpus ({G}er{P}ar{C}or) Reloaded},
  url       = {https://aclanthology.org/2024.lrec-main.681},
  pdf       = {https://aclanthology.org/2024.lrec-main.681.pdf},
  poster    = {https://www.texttechnologylab.org/wp-content/uploads/2024/05/GerParCor_Reloaded_Poster.pdf},
  video     = {https://www.youtube.com/watch?v=5X-w_oXOAYo},
  keywords  = {gerparcor,corpus},
  year      = {2024}
}

2023

Alexander Mehler, Mevlüt Bagci, Alexander Henlein, Giuseppe Abrami, Christian Spiekermann, Patrick Schrottenbacher, Maxim Konca, Andy Lücking, Juliane Engel, Marc Quintino, Jakob Schreiber, Kevin Saukel and Olga Zlatkin-Troitschanskaia. 2023. A Multimodal Data Model for Simulation-Based Learning with Va.Si.Li-Lab. Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, 539–565.
BibTeX
@inproceedings{Mehler:et:al:2023:a,
  abstract  = {Simulation-based learning is a method in which learners learn
               to master real-life scenarios and tasks from simulated application
               contexts. It is particularly suitable for the use of VR technologies,
               as these allow immersive experiences of the targeted scenarios.
               VR methods are also relevant for studies on online learning, especially
               in groups, as they provide access to a variety of multimodal learning
               and interaction data. However, VR leads to a trade-off between
               technological conditions of the observability of such data and
               the openness of learner behavior. We present Va.Si.Li-Lab, a VR-L
               ab for Simulation-based Learn ing developed to address this trade-off.
               Va.Si.Li-Lab uses a graph-theoretical model based on hypergraphs
               to represent the data diversity of multimodal learning and interaction.
               We develop this data model in relation to mono- and multimodal,
               intra- and interpersonal data and interleave it with ISO-Space
               to describe distributed multiple documents from the perspective
               of their interactive generation. The paper adds three use cases
               to motivate the broad applicability of Va.Si.Li-Lab and its data
               model.},
  address   = {Cham},
  author    = {Mehler, Alexander and Bagci, Mevl{\"u}t and Henlein, Alexander
               and Abrami, Giuseppe and Spiekermann, Christian and Schrottenbacher, Patrick
               and Konca, Maxim and L{\"u}cking, Andy and Engel, Juliane and Quintino, Marc
               and Schreiber, Jakob and Saukel, Kevin and Zlatkin-Troitschanskaia, Olga},
  booktitle = {Digital Human Modeling and Applications in Health, Safety, Ergonomics
               and Risk Management},
  editor    = {Duffy, Vincent G.},
  isbn      = {978-3-031-35741-1},
  pages     = {539--565},
  publisher = {Springer Nature Switzerland},
  title     = {A Multimodal Data Model for Simulation-Based Learning with Va.Si.Li-Lab},
  year      = {2023},
  doi       = {10.1007/978-3-031-35741-1_39}
}
Giuseppe Abrami, Alexander Mehler, Mevlüt Bagci, Patrick Schrottenbacher, Alexander Henlein, Christian Spiekermann, Juliane Engel and Jakob Schreiber. 2023. Va.Si.Li-Lab as a Collaborative Multi-User Annotation Tool in Virtual Reality and Its Potential Fields of Application. Proceedings of the 34th ACM Conference on Hypertext and Social Media.
BibTeX
@inproceedings{Abrami:et:al:2023,
  author    = {Abrami, Giuseppe and Mehler, Alexander and Bagci, Mevl\"{u}t and Schrottenbacher, Patrick
               and Henlein, Alexander and Spiekermann, Christian and Engel, Juliane
               and Schreiber, Jakob},
  title     = {Va.Si.Li-Lab as a Collaborative Multi-User Annotation Tool in
               Virtual Reality and Its Potential Fields of Application},
  year      = {2023},
  isbn      = {9798400702327},
  publisher = {Association for Computing Machinery},
  address   = {New York, NY, USA},
  url       = {https://doi.org/10.1145/3603163.3609076},
  doi       = {10.1145/3603163.3609076},
  abstract  = {During the last thirty years a variety of hypertext approaches
               and virtual environments -- some virtual hypertext environments
               -- have been developed and discussed. Although the development
               of virtual and augmented reality technologies is rapid and improving,
               and many technologies can be used at affordable conditions, their
               usability for hypertext systems has not yet been explored. At
               the same time, even for virtual three-dimensional virtual and
               augmented environments, there is no generally accepted concept
               that is similar or nearly as elegant as hypertext. This gap will
               have to be filled in the next years and a good concept should
               be developed; in this article we aim to contribute in this direction
               and also introduce a prototype for a possible implementation of
               criteria for virtual hypertext simulations.},
  booktitle = {Proceedings of the 34th ACM Conference on Hypertext and Social Media},
  articleno = {22},
  numpages  = {9},
  keywords  = {VaSiLiLab, virtual hypertext, virtual reality, virtual reality simulation, authoring system},
  location  = {Rome, Italy},
  series    = {HT '23},
  pdf       = {https://dl.acm.org/doi/pdf/10.1145/3603163.3609076}
}
Alexander Henlein, Andy Lücking, Mevlüt Bagci and Alexander Mehler. 2023. Towards grounding multimodal semantics in interaction data with Va.Si.Li-Lab. Proceedings of the 8th Conference on Gesture and Speech in Interaction (GESPIN).
BibTeX
@inproceedings{Henlein:et:al:2023c,
  title     = {Towards grounding multimodal semantics in interaction data with Va.Si.Li-Lab},
  author    = {Henlein, Alexander and Lücking, Andy and Bagci, Mevlüt and Mehler, Alexander},
  booktitle = {Proceedings of the 8th Conference on Gesture and Speech in Interaction (GESPIN)},
  location  = {Nijmegen, Netherlands},
  year      = {2023},
  keywords  = {vasililab},
  pdf       = {https://www.gespin2023.nl/documents/talks_and_posters/GeSpIn_2023_papers/GeSpIn_2023_paper_1692.pdf}
}

2022

Giuseppe Abrami, Mevlüt Bagci, Leon Hammerla and Alexander Mehler. 2022. German Parliamentary Corpus (GerParCor). Proceedings of the Language Resources and Evaluation Conference, 1900–1906.
BibTeX
@inproceedings{Abrami:Bagci:Hammerla:Mehler:2022,
  author    = {Abrami, Giuseppe and Bagci, Mevlüt and Hammerla, Leon and Mehler, Alexander},
  title     = {German Parliamentary Corpus (GerParCor)},
  booktitle = {Proceedings of the Language Resources and Evaluation Conference},
  year      = {2022},
  address   = {Marseille, France},
  publisher = {European Language Resources Association},
  pages     = {1900--1906},
  abstract  = {Parliamentary debates represent a large and partly unexploited
               treasure trove of publicly accessible texts. In the German-speaking
               area, there is a certain deficit of uniformly accessible and annotated
               corpora covering all German-speaking parliaments at the national
               and federal level. To address this gap, we introduce the German
               Parliamentary Corpus (GerParCor). GerParCor is a genre-specific
               corpus of (predominantly historical) German-language parliamentary
               protocols from three centuries and four countries, including state
               and federal level data. In addition, GerParCor contains conversions
               of scanned protocols and, in particular, of protocols in Fraktur
               converted via an OCR process based on Tesseract. All protocols
               were preprocessed by means of the NLP pipeline of spaCy3 and automatically
               annotated with metadata regarding their session date. GerParCor
               is made available in the XMI format of the UIMA project. In this
               way, GerParCor can be used as a large corpus of historical texts
               in the field of political communication for various tasks in NLP.},
  url       = {https://aclanthology.org/2022.lrec-1.202}
  poster    = {https://www.texttechnologylab.org/wp-content/uploads/2022/06/GerParCor_LREC_2022.pdf},
  keywords  = {gerparcor},
  pdf       = {http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.202.pdf}
}