Search results
Results: 31
Number of items: 31
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Roothaert, R., Schlobach, S., Massacci, F., & Stork, L. (2025). TIDO: The Threat Intelligence Decision Ontology. In K-CAP '25: Proceedings of the 13th Knowledge Capture Conference 2025 : Dayton, Ohio, USA (pp. 82-89). Association for Computing Machinery. https://doi.org/10.1145/3731443.3771351 -
Feng, R., Acar, E., Wang, Y., Schlobach, S., Liu, W., & Ding, W. (2022). Computing Sufficient and Necessary Conditions in CTL: A Forgetting Approach. Information Sciences, 616, 474-504. https://doi.org/10.1016/j.ins.2022.10.124
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Akata, Z., Balliet, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., Hung, H., Jonker, C., Monz, C., Neerincx, M., Oliehoek, F., Prakken, H., Schlobach, S., van der Gaag, L., van Harmelen, F., ... Welling, M. (2020). A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(8), 18-28. https://doi.org/10.1109/MC.2020.2996587 -
van der Meulen, A., Kwisthout, J., ten Teije, A., Schlobach, S., van Splunter, S., Winands, M., van Netten, S., Visser, A., van Someren, M., Dastani, M., & Dignum, F. (2018). Frame of Reference - Bachelor’s and Master’s Programmes in Artificial Intelligence: The Dutch Perspective. Kunstmatige Intelligentie Opleidingen Nederland (KION). -
Visser, A., De Jong, R., Beks, W., Schlobach, S., van Rooij, R., Homburg, A.-J., van Someren, M., van Maanen, L., & Sluijter, B. (2017). Naar een nieuw curriculum voor de bachelor Kunstmatige Intelligentie. (1.9.1 ed.) UvA. https://staff.fnwi.uva.nl/a.visser/activities/CurriculumCommissieRapport9maart.pdf -
van Wierst, P., Vrijenhoek, S., Schlobach, S., & Betti, A. (2016). Phil@Scale: Computational Methods within Philosophy. In L. Wieneke, C. Jones, M. Düring, F. Armaselu, & R. Leboutte (Eds.), Proceedings of the Third Conference on Digital Humanities in Luxembourg with a Special Focus on Reading Historical Sources in the Digital Age: Luxembourg, Luxembourg, December 5-6, 2013 (CEUR Workshop Proceedings; Vol. 1681). CEUR-WS. http://ceur-ws.org/Vol-1681/Wierst_et_al_Philo_at_scale.pdf -
Hoekstra, R., Magliacane, S., Rietveld, L., de Vries, G., Wibisono, A., & Schlobach, S. (2015). Hubble: Linked Data Hub for Clinical Decision Support. In E. Simperl, B. Norton, D. Mladenic, E. Della Valle, I. Fundulaki, A. Passant, & R. Troncy (Eds.), The Semantic Web: ESWC 2012 Satellite Events: ESWC 2012 Satellite Events, Heraklion, Crete, Greece, May 27-31, 2012 : revised selected papers (pp. 458-462). (Lecture Notes in Computer Science; Vol. 7540). Springer. https://doi.org/10.1007/978-3-662-46641-4_45
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Rietveld, L., Hoekstra, R., Schlobach, S., & Guéret, C. (2014). Structural Properties as Proxy for Semantic Relevance in RDF Graph Sampling. In P. Mika, T. Tudorache, A. Bernstein, C. Welty, C. Knoblock, D. Vrandečić, P. Groth, N. Noy, K. Janowicz, & C. Goble (Eds.), The Semantic Web – ISWC 2014: 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014: proceedings (Vol. 2, pp. 81-96). (Lecture Notes in Computer Science; Vol. 8797). Springer. https://doi.org/10.1007/978-3-319-11915-1_6
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Beek, W., Groth, P., Schlobach, S., & Hoekstra, R. (2014). A Web Observatory for the Machine Processability of Structured Data on the Web. In WebSci'14: proceedings of the 2014 ACM Web Science Conference: June 23-26, 2014, Bloomington, IN, USA (pp. 249-250). Association for Computing Machinery. https://doi.org/10.1145/2615569.2615654 -
Meroño-Peñuela, A., Guéret, C., Hoekstra, R., & Schlobach, S. (2013). Detecting and Reporting Extensional Concept Drift in Statistical Linked Data. In S. Capadisli, F. Cotton, R. Cyganiak, A. Haller, A. Hamilton, & R. Troncy (Eds.), Proceedings of the 1st International Workshop on Semantic Statistics: co-located with 12th International Semantic Web Conference (ISWC 2013) : Sydney, Australia, October 11th, 2013 Article 10 (CEUR Workshop Proceedings; Vol. 1549). CEUR-WS. http://ceur-ws.org/Vol-1549/article-10.pdf
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