Search results
Results: 116
Number of items: 116
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Nevin, J., Groth, P., & Lees, M. (2023). An approach for analysing the impact of data integration on complex network diffusion models. Journal of complex networks, 11(4), Article cnad025. https://doi.org/10.1093/comnet/cnad025 -
Ayoughi, M., Mettes, P., & Groth, P. (2023). Self-Contained Entity Discovery from Captioned Videos. ACM Transactions on Multimedia Computing Communications and Applications, 19(5s), Article 177. https://doi.org/10.1145/3583138
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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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Karabulut, E., Degeler, V., & Groth, P. (2023). Semantic Association Rule Learning from Time Series Data and Knowledge Graphs. In A. Waaler, E. Kharlamov, B. Zhou, A. Soylu, D. Kyritsis, D. Roman, O. Savkovic, & S. Staab (Eds.), Proceedings of the Second International Workshop on Semantic Industrial Information Modelling (SemIIM 2023) : co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Greece, Athens, 7 November 2023 Article 3 (CEUR workshop proceedings; Vol. 3647). CEUR-WS. https://doi.org/10.48550/arXiv.2310.07348
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Li, X., Polat, F., & Groth, P. (2023). Do Instruction-tuned Large Language Models Help with Relation Extraction? In S. Razniewski, J.-C. Kalo, S. Singhania, & J. Z. Pan (Eds.), Joint proceedings of the 1st workshop on Knowledge Base Construction from Pre-Trained Language Models (KBC-LM) and the 2nd challenge on Language Models for Knowledge Base Construction (LM-KBC): co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 6, 2023 Article 15 (CEUR Workshop Proceedings; Vol. 3577). CEUR-WS. https://ceur-ws.org/Vol-3577/paper15.pdf
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Li, X., Hughes, A., Llugiqi, M., Polat, F., Groth, P., & Ekaputra, F. J. (2023). Knowledge-centric Prompt Composition for Knowledge Base Construction from Pre-trained Language Models. In S. Razniewski, J.-C. Kalo, S. Singhania, & J. Z. Pan (Eds.), Joint proceedings of the 1st workshop on Knowledge Base Construction from Pre-Trained Language Models (KBC-LM) and the 2nd challenge on Language Models for Knowledge Base Construction (LM-KBC): co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Athens, Greece, November 6, 2023 Article 3 (CEUR Workshop Proceedings; Vol. 3577). CEUR-WS. https://ceur-ws.org/Vol-3577/paper3.pdf
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Grafberger, S., Guha, S., Groth, P., & Schelter, S. (2023). Mlwhatif: What If You Could Stop Re-Implementing Your Machine Learning Pipeline Analyses over and Over? Proceedings of the VLDB Endowment, 16(12), 4002–4005. https://doi.org/10.14778/3611540.3611606
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Allen, B. P., Stork, L., & Groth, P. (2023). Knowledge Engineering using Large Language Models. Transactions on Graph Data and Knowledge, 1(1), Article 3. https://doi.org/10.4230/TGDK.1.1.3
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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
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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
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