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Data Science Chair - Data Science ChairData Science Chair - Data Science Chair HomeNewsArchivResearchKnowledge Enriched Machine LearningLarge Language ModelsTime Series & Sequence ModelingDeep Representation and Metric LearningDeep Learning for Imbalanced DataExplainable AIRankingPublicationsDatasetsDynaBenchNIDS-DSnetflow-ganHarryMotionsTools and WebpagesProjectsNatural Language ProcessingLitBERTKILiModMOTIVDetecting Scenes in FictionMachine Learning and Knowledge GraphsAnalysing Comments on Twitch.tvCLiGS (concluded)Kallimachos (concluded)Kallimachos - PublicationsGerman Novel DatasetTIR2015 Genre dataML for Ecosystems and Climate ModelingBigData@Geo 2.0BigData@GeoBeeConnectedwe4beep2Map (concluded)EveryAware (concluded)ML on Publication DataBibSonomyPublicationsHydrASREGIO (concluded)PUMA (concluded)PoSTs I & II (concluded)PublicationsBib100ML for Recommender SystemsPublicationsadidas (concluded)Physics Informed Deep LearningMAGNETP-BIM (concluded)KI@FlowChief (concluded)AI@Knauf (concluded)Mozart & KI (concluded)Mozart Genom Web-AppML for Network Security & Fraud DetectionOccupational Fraud DetectionDeepScan (concluded)ERP Fraud DataERP Fraud GameXAI Evaluation DatasetsML for Medical & Biological DataTissueNetDZ.PTMLectures2024 WSSeminar: Ausgewählte Themen des Machine Learning (BA)DatenbankenMachine Learning for Time Series and Anomaly DetectionGrundlagen der Algorithmen und Datenstrukturen2024 SSSeminar + Praktikum: Machine Learning for Cyber SecurityData Science (ehemals Data Mining)Machine Learning for Natural Language ProcessingPraktikum: Machine Learning for Time Series AnalysisSeminar: Ausgewählte Themen des Machine Learning (BA and MA)Praktikum: XtAI Lab2023 WSMachine Learning for Time Series and Anomaly DetectionSprachverarbeitung und Text MiningGrundlagen der Algorithmen und DatenstrukturenInteractive Artificial IntelligenceSeminar: Ausgewählte Themen des Machine Learning (BA and MA)Praktikum: Natural Language ProcessingXtAI Lab2023 SSData Science (ehemals Data Mining)Machine Learning for Natural Language ProcessingPraktikum: Machine Learning for Time Series AnalysisSeminar: Ausgewählte Themen des Machine Learning (BA and MA)XtAI Lab2022 WSGrundlagen der Algorithmen und DatenstrukturenInteractive Artificial IntelligenceSeminar: Ausgewählte Themen des Machine Learning (BA and MA)Praktikum: Natural Language ProcessingXtAI LabDatenbanken2022 SSMachine Learning for Natural Language ProcessingInformation RetrievalData MiningPraktikum: Machine Learning for Time Series AnalysisSeminar: Ausgewählte Themen des Machine Learning (BA)Seminar: Ausgewählte Themen des Machine Learning (MA)XtAI Lab2021 WSGrundlagen der Algorithmen und DatenstrukturenSprachverarbeitung und Text MiningInteractive Artificial IntelligencePraktikum: Natural Language ProcessingSeminar: Ausgewählte Themen des Machine Learning (BA)Seminar: Ausgewählte Themen des Machine Learning (MA)XtAI Lab2021 SSMachine Learning for Natural Language ProcessingInformation RetrievalData MiningPraktikum: Machine Learning for Time Series AnalysisPraktikum: Machine Learning for RecommendationSeminar: Ausgewählte Themen des Machine Learning (BA)Seminar: Ausgewählte Themen des Machine Learning (MA)2020 WSGrundlagen der Algorithmen und DatenstrukturenPraktikum: Natural Language ProcessingDatenbankenSeminar: Ausgewählte Themen des Machine LearningSeminar: Musik und Maschinelles Lernen2020 SSPraktikum: Natural Language ProcessingSeminar: Ausgewählte Themen des Machine LearningInformation RetrievalData MiningMachine Learning for Natural Language ProcessingArchiv2019 WSGrundlagen der Algorithmen und DatenstrukturenInformatik und EthikPraktikum: Natural Language ProcessingSeminar: Ausgewählte Themen des Machine LearningSprachverarbeitung und Text Mining2019 SSPraktikum: Natural Language ProcessingMachine Learning for Natural Language ProcessingSeminar: Ausgewählte Themen des Machine LearningData MiningInformation Retrieval2018 WSGrundlagen der Algorithmen und DatenstrukturenDatenbankenSeminar: Ausgewählte Themen des Machine LearningPraktikum: Natural Language Processing2018 SSData MiningInformation RetrievalMachine Learning for Natural Language ProcessingSeminar: Ausgewählte Themen des Machine LearningPraktikum: Natural Language Processing2017 WSSeminar: Ausgewählte Themen des Machine Learning2017 SSEinführendes Programmierpraktikum (Wiinf/MCS/WiMa)Data MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02016 WSEinführendes Programmierpraktikum (Wiinf/MCS/WiMa)Sprachverarbeitung und Text MiningGrundlagen der Algorithmen und DatenstrukturenSeminar: Ausgewählte Themen des Web 2.02016 SSEinführendes Programmierpraktikum (Wiinf/MCS/WiMa)Data MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02015 WSGrundlagen der Algorithmen und DatenstrukturenSeminar: Ausgewählte Themen des Web 2.02015 SSData MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02014 WSGrundlagen der Algorithmen und DatenstrukturenSeminar: Ausgewählte Themen des Web 2.02014 SSData MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02013 WSAlgorithmen und Datenstrukturen für Wirtschaftsinformatiker und Mensch-Computer-SystemeSeminar: Ausgewählte Themen des Web 2.02013 SSData MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02012 WSSeminar: Ausgewählte Themen des Web 2.02012 SSData MiningInformation RetrievalSeminar: Ausgewählte Themen des Web 2.02011 WSSeminarTheses & PracticaOpen TopicsNatural Language ProcessingML for Ecosystems & Climate ModelingML for Publication DataRecommender SystemsPhysics Informed Deep LearningSecurity & FraudML for Biological & Medical DataMisc.Completed ThesesStaffProf. Dr. Andreas HothoPublications by Andreas HothoDr.-Ing. Anna KrauseDeep Learning for Dynamical Systems GroupDr. Daniel SchlörLena Hettinger, Dipl.-Math.Andrzej Dulny, M.Sc.Elisabeth Fischer, M.Sc.Jonas Kaiser, M.Sc.Florian Gallusser, M.Sc.Tobias Koopmann, M.Sc.Janna Omeliyanenko, M.Sc.Jan Pfister, M.Sc.Martin Rackl, M.Sc.Maximilian Wolf, M.Sc.Sebastian Wankerl, M.Sc.Albin Zehe, M.Sc.PublicationsFormer staffJulian Tritscher, M.Sc.Pascal Janetzky, M.Sc.Padraig Davidson, M.Sc.Dr. Melanie SchallerKonstantin Kobs, M.Sc.Alexander Dallmann, Dipl. Inf.Dr. Michael Steininger, M.Sc.Florian Buckermann, M.Sc.Daniel Zoller, M.Sc.PublicationsTeachingFlorian Lautenschlager, M.Sc.Dr. Martin BeckerDr. Thomas NieblerTeachingPublicationsSupplementary MaterialsOpen Positions Intern Intern HomeNewsArchivResearchKnowledge Enriched Machine LearningLarge Language ModelsTime Series & Sequence ModelingDeep Representation and Metric LearningDeep Learning for Imbalanced DataExplainable AIRankingPublicationsDatasetsTools and WebpagesProjectsNatural Language ProcessingML for Ecosystems and Climate ModelingML on Publication DataML for Recommender SystemsPhysics Informed Deep LearningML for Network Security & Fraud DetectionML for Medical & Biological DataLectures2024 WS2024 SS2023 WS2023 SS2022 WS2022 SS2021 WS2021 SS2020 WS2020 SSArchivTheses & PracticaOpen TopicsCompleted ThesesStaffProf. Dr. Andreas HothoDr.-Ing. Anna KrauseDr. Daniel SchlörLena Hettinger, Dipl.-Math.Andrzej Dulny, M.Sc.Elisabeth Fischer, M.Sc.Jonas Kaiser, M.Sc.Florian Gallusser, M.Sc.Tobias Koopmann, M.Sc.Janna Omeliyanenko, M.Sc.Jan Pfister, M.Sc.Martin Rackl, M.Sc.Maximilian Wolf, M.Sc.Sebastian Wankerl, M.Sc.Albin Zehe, M.Sc.Former staffOpen Positions Animation stoppen Data Science Chair Data Science Chair About Us The Data Science Chair (computer science institute JMU) is a highly interdisciplinary group of researchers led by Prof. Andreas Hotho and member of CAIDAS. We are active in data science and machine learning research with focus on deep learning and applications in multiple domains. Address We have moved! We're now located at: University of Würzburg Data Science Chair (Computer Science X) Emil-Fischer-Straße 50 97074 Würzburg Phone.: +49 931 31-89675 sekretariat.lsx@uni-wuerzburg.de We are part of: Faculty of Mathematics and Computer Science Institute of Computer Science CAIDAS Recent Publications Pollice Verso at {S}em{E}val-2024 Task 6: The {R}oman Empire Strikes Back. Kobs, Konstantin; Pfister, Jan; Hotho, Andreas. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), A. K. Ojha, A. S. Do{\u{g}}ru{ö}z, H. Tayyar Madabushi, G. Da San Martino, S. Rosenthal, A. Ros{á} (eds.), pp. 1529–1536. Association for Computational Linguistics, Mexico City, Mexico, 2024 [ Download ] [ BibSonomy-Post ] {S}uper{GLEB}er: {G}erman Language Understanding Evaluation Benchmark. Pfister, Jan; Hotho, Andreas. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), K. Duh, H. Gomez, S. Bethard (eds.), pp. 7897–7916. Association for Computational Linguistics, Mexico City, Mexico, 2024 [ Download ] [ BibSonomy-Post ] {O}tterly{O}bsessed{W}ith{S}emantics at {S}em{E}val-2024 Task 4: Developing a Hierarchical Multi-Label Classification Head for Large Language Models. Wunderle, Julia; Schubert, Julian; Cacciatore, Antonella; Zehe, Albin; Pfister, Jan; Hotho, Andreas. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), A. K. Ojha, A. S. Do{\u{g}}ru{ö}z, H. Tayyar Madabushi, G. Da San Martino, S. Rosenthal, A. Ros{á} (eds.), pp. 602–612. Association for Computational Linguistics, Mexico City, Mexico, 2024 [ Download ] [ BibSonomy-Post ] From Chat to Publication Management: Organizing your related work using BibSonomy & LLMs. Völker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, of CHIIR ’24, pp. 386–390. Association for Computing Machinery, , Sheffield, United Kingdom, , 2024 [ Download ] [ BibSonomy-Post ] Generative Inpainting for Shapley-Value-Based Anomaly Explanation. Tritscher, Julian; Lissmann, Philip; Wolf, Maximilian; Krause, Anna; Hotho, Andreas; Schlör, Daniel. In The World Conference on eXplainable Artificial Intelligence (xAI 2024) - to appear. 2024 [ Download ] [ BibSonomy-Post ] Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. Seufert, Michael; Dietz, Katharina; Wehner, Nikolas; Geißler, Stefan; Schüler, Joshua; Wolz, Manuel; Hotho, Andreas; Casas, Pedro; Hoßfeld, Tobias; Feldmann, Anja. In IEEE Transactions on Network and Service Management, pp. 1–1. 2024 [ Download ] [ BibSonomy-Post ] CompTrails: comparing hypotheses across behavioral networks. Koopmann, Tobias; Becker, Martin; Lemmerich, Florian; Hotho, Andreas. In Data Mining and Knowledge Discovery. 2024 [ Download ] [ BibSonomy-Post ] Global Vegetation Modeling with Pre-Trained Weather Transformers. Janetzky, Pascal; Gallusser, Florian; Hentschel, Simon; Hotho, Andreas; Krause, Anna. 2024 [ Download ] [ BibSonomy-Post ] From Chat to Publication Management: Organizing your related work using BibSonomy \& LLMs. V{ö}lker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. In Proceedings of the 2024 Conference on Human Information Interaction and Retrieval, of CHIIR ’24, pp. 386–390. Association for Computing Machinery, , Sheffield, United Kingdom, , 2024 [ Download ] [ BibSonomy-Post ] BibSonomy Meets ChatLLMs for Publication Management: From Chat to Publication Management: Organizing your related work using BibSonomy & LLMs. Völker, Tom; Pfister, Jan; Koopmann, Tobias; Hotho, Andreas. 2024 [ Download ] [ BibSonomy-Post ] Data Generation for Explainable Occupational Fraud Detection. Tritscher, Julian; Wolf, Maximilian; Krause, Anna; Hotho, Andreas; Schlör, Daniel. In 47th German Conference on Artificial Intelligence (KI 2024) - to appear. 2024 [ Download ] [ BibSonomy-Post ] Modeling and Analyzing the Influence of Non-Item Pages on Sequential Next-Item Prediction. Fischer, Elisabeth; Schlör, Daniel; Zehe, Albin; Hotho, Andreas. 2024 [ BibSonomy-Post ] Liquor-HGNN: A heterogeneous graph neural network for leakage detection in water distribution networks. Schaller, Melanie; Steininger, Michael; Dulny, Andrzej; Schlör, Daniel; Hotho, Andreas. In LWDA’23: Lernen, Wissen, Daten, Analysen. October 09--11, 2023, Marburg, Germany, M. Leyer (ed.). 2023 [ Download ] [ BibSonomy-Post ] Multi-Task Transformer Visualization to build Trust for Clinical Outcome Prediction. Antweiler, Dario; Gallusser, Florian; Fuchs, Georg. In 2023 Workshop on Visual Analytics in Healthcare (VAHC), pp. 21–26. 2023 [ BibSonomy-Post ] Pointer Networks: A Unified Approach to Extracting {G}erman Opinions. Wunderle, Julia; Pfister, Jan; Hotho, Andreas. In Proceedings of the 19th Conference on Natural Language Processing (KONVENS 2023), M. Georges, A. Herygers, A. Friedrich, B. Roth (eds.), pp. 127–138. Association for Computational Lingustics, Ingolstadt, Germany, 2023 [ Download ] [ BibSonomy-Post ] Zero-Shot Clickbait Spoiling by Rephrasing Titles as Questions. Wangsadirdja, Dirk; Pfister, Jan; Kobs, Konstantin; Hotho, Andreas. In Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), pp. 1090–1095. Association for Computational Linguistics, Toronto, Canada, 2023 [ Download ] [ BibSonomy-Post ] Feature relevance XAI in anomaly detection: Reviewing approaches and challenges. Tritscher, Julian; Krause, Anna; Hotho, Andreas. In Frontiers in Artificial Intelligence, Vol. 6. 2023 [ Download ] [ BibSonomy-Post ] ConvMOS: climate model output statistics with deep learning. Steininger, Michael; Abel, Daniel; Ziegler, Katrin; Krause, Anna; Paeth, Heiko; Hotho, Andreas. In Data Mining and Knowledge Discovery, Vol. 37, Issue 1, pp. 136–166. 2023 [ Download ] [ BibSonomy-Post ] Evaluating feature relevance XAI in network intrusion detection. Tritscher, Julian; Wolf, Maximilian; Hotho, Andreas; Schlör, Daniel. In The World Conference on eXplainable Artificial Intelligence (xAI 2023). 2023 [ Download ] [ BibSonomy-Post ] Can Neural Networks Distinguish High-school Level Mathematical Concepts?. Wankerl, Sebastian; Dulny, Andrzej; Götz, Gerhard; Hotho, Andreas. In Accepted at ICDM. 2023 [ BibSonomy-Post ] News Successful Conference Week with LWDA and KI We're looking back on an amazing week of presentations and discussions at both the LWDA and KI conferences, plus all the great workshops! A big thanks to all the participants and helpers who made the conference a success and for the awesome chance to share ideas and knowledge. Mehr KI24 Kicks Off at the JMU in Würzburg The KI24 conference kicked off today at the University of Würzburg's Computer Science building, bringing together AI experts and researchers from around the world. The event features keynotes, workshops, and discussions on the latest developments in… Mehr Our paper "Adapting Sequential Recommender Models to Content Recommendation in Chat Data using Non-Item Page-Models" has been accepted at the KARS workshop at RecSys 24 In our work "Adapting Sequential Recommender Models to Content Recommendation in Chat Data using Non-Item Page-Models", we adapt sequential recommender models for content recommendation in twitch and multiple other chat systems by modeling messages as non-item pages with pretrained embeddings.     Mehr Research Find out more about our research topics!  Projects Our projects and cooperations! Publications Check out our publication records! Staff Get to know us! Head of Chair: Prof. Andreas Hotho Dr. Anna Krause Dr. Daniel Schlör Teaching Check out our lectures and open topics for theses and practica! Lectures Theses & Practica Jobs We offer various jobs for interested BA and MA students - research related, help with lectures or administrative tasks. Hinweis zum Datenschutz Mit 'OK' verlassen Sie die Seiten der Universität Würzburg und werden zu Facebook weitergeleitet. Informationen zu den dort erfassten Daten und deren Verarbeitung finden Sie in deren Datenschutzerklärung. OKAbbrechen Hinweis zum Datenschutz Mit 'OK' verlassen Sie die Seiten der Universität Würzburg und werden zu Twitter weitergeleitet. Informationen zu den dort erfassten Daten und deren Verarbeitung finden Sie in deren Datenschutzerklärung. 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