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Results: 32
Number of items: 32
  • Open Access
    Huang, Y., Karabulut, E., & Degeler, V. (2025). Large Language Model for Ontology Learning In Drinking Water Distribution Network Domain. In C. Badenes-Olmedo, I. Novalija, E. Daga, L. Stork, R. G. Pillai, L. Dierickx, B. Kruit, V. Degeler, J. Moreira, B. Zhang, R. Alharbi, Y. He, A. Graciotti, A. Morales Tirado, V. Presutti, & E. Motta (Eds.), Joint Proceedings of Posters, Demos, Workshops, and Tutorials of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-PDWT 2024): co-located with 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2024) : Amsterdam, Netherlands, November 26-28, 2024 (CEUR Workshop Proceedings; Vol. 3967). CEUR-WS. https://ceur-ws.org/Vol-3967/ELMKE_2024_paper_1.pdf
  • Open Access
    Karabulut, E., Daza, D., Groth, P., & Degeler, V. (2025). Discovering Association Rules in High-Dimensional Small Tabular Data. In A. Agiollo, E. Bardhi, G. Ciatto, S. Dumancic, & G. Marra (Eds.), Proceedings of the 1st International Workshop on Advanced Neuro-Symbolic Applications: co-located with the 28th European Conference on Artificial Intelligence (ECAI 2025) : Bologna, Italy, October 26, 2025 (pp. 105-113). (CEUR Workshop Proceedings; Vol. 4125). CEUR-WS. https://ceur-ws.org/Vol-4125/paper_26.pdf
  • Tello, A., Truong, H., Lazovik, A., & Degeler, V. (2024, May 27). Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11353195
  • Open Access
    Khalil, A., Lotfian Delouee, M., Degeler, V., Meuser, T., Fernandez Anta, A., & Koldehofe, B. (2024). Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks. In 2024 22nd Mediterranean Communication and Computer Networking Conference: MedComNet 2024 : Nice, France, 11-13 June 2024 (pp. 55-64). IEEE. https://doi.org/10.1109/MedComNet62012.2024.10578208
  • Open Access
    Hadadian Nejad Yousefi, M., Degeler, V., & Lazovik, A. (2024). Self-Adaptive Service Selection for Machine Learning Continuous Delivery. In R. N. Chang, C. K. Chang, Z. Jiang, J. Yang, Z. Jin, M. Sheng, J. Fan, K. Fletcher, Q. He, C. Ardagna, J. Yang, J. Yin, Z. Wang, A. Beheshti, S. Russo, N. Atukorala, J. Wu, P. S. Yu, H. Ludwig, S. Reiff-Marganiec, W. E. Zhang, A. Sailer, N. Bena, K. Li, Y. Watanabe, T. Zhao, S. Wang, Z. Tu, Y. Wang, ... K. Wei (Eds.), 2024 IEEE International Conference on Web Services: IEEE ICWS 2024 : Shenzhen, China, 7-13 July 2024 : proceedings (pp. 1048-1056). IEEE Computer Society. https://doi.org/10.1109/ICWS62655.2024.00123
  • Open Access
    Lotfian Delouee, M., Pernes, D. G., Degeler, V., & Koldehofe, B. (2024). Poster: Towards Federated LLM-Powered CEP Rule Generation and Refinement. In DEBS 2024: Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems : June 25-29, 2024, Villeurbanne, France (pp. 185-186). Association for Computing Machinery. https://doi.org/10.1145/3629104.3672429
  • Open Access
    van Etten, T., Degeler, V., & Luo, D. (2024). Large-Scale Forecasting of Electric Vehicle Charging Demand Using Global Time Series Modeling. In A. Vinel, K. Berns, J. Ploeg, & O. Gusikhin (Eds.), VEHITS 2024: proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems : 2-4 May, 2024, Angers, France (pp. 40-51). SciTePress. https://doi.org/10.5220/0012555400003702
  • Open Access
    Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, 153, 442-456. https://doi.org/10.1016/j.future.2023.12.013
  • Open Access
    Lotfian Delouee, M., Degeler, V., Amthor, P., & Koldehofe, B. (2024). APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems. In G. Lenzini, P. Mori, & S. Furnell (Eds.), ICISSP 2024: Proceedings of the 10th International Conference on Information Systems Security and Privacy : 26-28 February, 2024, Rome, Italy (pp. 486-497). SciTePress. https://doi.org/10.5220/0012358700003648
  • Open Access
    Tello, A., Degeler, V., & Lazovik, A. (2024). Too Good To Be True: accuracy overestimation in (re)current practices for Human Activity Recognition. In 2024 IEEE International Conference on Pervasive Computing and Communications workshops and other affiliated events (PerCom workshops 2024) : Biarritz, France, 11-15 March 2024 (pp. 511-517). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503465
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