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Results: 125
Number of items: 125
  • Open Access
    Zhang, Z., Groth, P., Calixto, I., & Schelter, S. (2024). Directions Towards Efficient and Automated Data Wrangling with Large Language Models. In 2024 IEEE 40th International Conference on Data Engineering Workshops: ICDEW 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 301-304). IEEE Computer Society. https://doi.org/10.1109/ICDEW61823.2024.00044
  • Open Access
    Soiland-Reyes, S., Goble, C., & Groth, P. (2024). Evaluating FAIR Digital Object and Linked Data as distributed object systems. PeerJ Computer Science, 10, Article e1781. https://doi.org/10.7717/PEERJ-CS.1781
  • Thanapalasingam, T., van Krieken, E., Bloem, P., & Groth, P. (2023, April 13). IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8039857
  • Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2023, July 21). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8172341
  • Thanapalasingam, T., van Krieken, E., Bloem, P., & Groth, P. (2023, April). IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14787483
  • Open Access
    Prieto, L., Den Boef, J., Groth, P., & Cornelisse, J. (2023). Parameter Efficient Node Classification on Homophilic Graphs. Transactions on Machine Learning Research, 2023, Article 640. https://openreview.net/forum?id=LIT8tjs6rJ
  • Open Access
    Simperl, E., Groth, P., Staab, S., Sabou, M., Blomqvist, E., & Allen, B. (2023). Knowledge Engineering with Language Models and Neural Methods. Dagstuhl Reports, 12(9), 93-96. https://doi.org/10.4230/DagRep.12.9.60
  • Open Access
    Polat, F., Tiddi, I., Groth, P., & Vossen, P. (2023). Improving Graph-to-Text Generation Using Cycle Training. In S. Carvalho, A. F. Khan, A. Ostroški Anić, B. Spahiu, J. Gracia, J. P. McCrae, D. Gromann, B. Heinisch, & A. Salgado (Eds.), Language, data and knowledge 2023: LDK 2023 : proceedings of the 4th Conference on Language, Data and Knowledge : 12-15 September 2023, Vienna, Austria (pp. 256-261). NOVA CLUNL. https://doi.org/10.34619/srmk-injj
  • Open Access
    Nevin, J., Groth, P., & Lees, M. (2023). Data Integration Landscapes: The Case for Non-optimal Solutions in Network Diffusion Models. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2023: 23rd International Conference, Prague, Czech Republic, July 3–5, 2023 : proceedings (Vol. I, pp. 494-508). (Lecture Notes in Computer Science; Vol. 14073). Springer. https://doi.org/10.1007/978-3-031-35995-8_35
  • Open Access
    Daza, D., Alivanistos, D., Mitra, P., Pijnenburg, T., Cochez, M., & Groth, P. (2023). BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. Journal of Biomedical Semantics, 14, Article 20. https://doi.org/10.1186/s13326-023-00301-y
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