de Camargo e Souza Câmara, I., &; Turhan, A.-Y. (2023). Deciding Subsumption in Defeasible $$\'6dathcal ELI_$$ with Typicality Models. In Logics in Artificial Intelligence. Springer Nature Switzerland.https://doi.org/10.1007/978-3-031-43619-2_36 

Gil, O. F., Patrizi, F., Perelli, G., &; Turhan, A.-Y. (2023). Optimal Alignment of Temporal Knowledge Bases. CoRR, abs/2307.15439.https://doi.org/10.48550/ARXIV.2307.15439 

Turhan, A.-Y. (2023). Brushing-up DLs to Cope with Imperfect Data (Abstract of Joint DL+NMR Invited Talk). In O. Kutz, C. Lutz, &; A. Ozaki (Eds.), Proceedings of the 36th International Workshop on Description Logics (DL 2023) co-located with the 20th International Conference on Principles of Knowledge Representation and Reasoning and the 21st International Workshop on Non-Monotonic Reasoning (KR 2023 and NMR 2023)., Rhodes, Greece, September 2-4, 2023 (Vol. 3515). CEUR-WS.org.

Tirtarasa, S., &; Turhan, A.-Y. (2022). Computing generalizations of temporal            ;5L            concepts with next and global. Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing.https://doi.org/10.1145/3477314.3507136 

Turhan, A.-Y. (2022). A Double Take at Conferences: The Hybrid Format. KI - Künstliche Intelligenz, 36(1), 1–4.https://doi.org/10.1007/s13218-022-00758-6 

de Camargo e Souza Câmara, I., &; Turhan, A.-Y. (2022). Rational Defeasible Subsumption in DLs with Nested Quantifiers: the Case of ELI\'70erp. In O. Arieli, G. Casini, &; L. Giordano (Eds.), Proceedings of the 20th International Workshop on Non-Monotonic Reasoning, NMR 2022, Part of the Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7-9, 2022 (Vol. 3197, pp. 159–162). CEUR-WS.org.

Tirtarasa, S., &; Turhan, A.-Y. (2022). Computing generalizations of temporal mph?5L concepts with next and global. In J. Hong, M. Bures, J. W. Park, &; T. Cerný (Eds.), SAC ’22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022 (pp. 903–910). ACM.https://doi.org/10.1145/3477314.3507136 

Governatori, G., &; Turhan, A.-Y. (Eds.). (2022). Rules and Reasoning - 6th International Joint Conference on Rules and Reasoning, RuleML+RR 2022, Berlin, Germany, September 26-28, 2022, Proceedings (Vol. 13752). Springer.https://doi.org/10.1007/978-3-031-21541-4 

Baader, F., Koopmann, P., Michel, F., Turhan, A.-Y., &; Zarrieß, B. (2022). Efficient TBox Reasoning with Value Restrictions Using the FL0wer Reasoner (Extended Abstract). In O. Arieli, M. Homola, J. C. Jung, &; M.-L. Mugnier (Eds.), Proceedings of the 35th International Workshop on Description Logics (DL 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022 (Vol. 3263). CEUR-WS.org.

Peñaloza, R., &; Turhan, A.-Y. (2022). User-aware Explications of Ontology Consequences: Levelling Technicality. In C. Beierle, M. Ragni, F. Stolzenburg, K. Sauerwald, &; M. Thimm (Eds.), Proceedings of the 8th Workshop on Formal and Cognitive Reasoning co-located with the 45th German Conference on Artificial Intelligence (KI 2022), Virtual Event, Trier, Germany, September 19, 2022 (Vol. 3242, pp. 90–101). CEUR-WS.org.

Tirtarasa, S., &; Turhan, A.-Y. (2022). A New Dimension to Generalization: Computing Temporal EL Concepts from Positive Examples (Extended Abstract). In O. Arieli, M. Homola, J. C. Jung, &; M.-L. Mugnier (Eds.), Proceedings of the 35th International Workshop on Description Logics (DL 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022 (Vol. 3263). CEUR-WS.org.

Baader, F., Koopmann, P., Michel, F., Turhan, A.-Y., &; Zarrieß, B. (2022). Efficient TBox Reasoning with Value Restrictions using the \'6dathscrF\'6dathscrL_\'6dbower Reasoner. Theory Pract. Log. Program., 22(2), 162–192.https://doi.org/10.1017/S1471068421000466 

Alrabbaa, C., Hieke, W., &; Turhan, A.-Y. (2021). Counter Model Transformation for Explaining Non-Subsumption in EL. In C. Beierle, M. Ragni, F. Stolzenburg, &; M. Thimm (Eds.), Proceedings of the 7th Workshop on Formal and Cognitive Reasoning co-located with the 44th German Conference on Artificial Intelligence (KI 2021), September 28, 2021 (Vol. 2961, pp. 9–22). CEUR-WS.org.

Gil, O. F., &; Turhan, A.-Y. (2021). Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics. Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, 6340–6348.https://doi.org/10.1609/AAAI.V35I7.16787 

Dubslaff, C., Koopmann, P., &; Turhan, A.-Y. (2021). Enhancing Probabilistic Model Checking with Ontologies. Formal Aspects Comput., 33(6), 885–921.https://doi.org/10.1007/S00165-021-00549-0 

Baader, F., Koopmann, P., Michel, F., Turhan, A.-Y., &; Zarrieß, B. (2021). Efficient TBox Reasoning with Value Restrictions using the \'6dathscrF\'6dathscrL_\'6dbower reasoner. CoRR, abs/2107.12877.

Baader, F., Borgwardt, S., Koopmann, P., Thost, V., &; Turhan, A.-Y. (2020). Semantic Technologies for Situation Awareness. Künstliche Intell., 34(4), 543–550.https://doi.org/10.1007/S13218-020-00694-3 

Dubslaff, C., Koopmann, P., &; Turhan, A.-Y. (2020). Give Inconsistency a Chance: Semantics for Ontology-Mediated Verification. In S. Borgwardt &; T. Meyer (Eds.), Proceedings of the 33rd International Workshop on Description Logics (DL 2020) co-located with the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR 2020), Online Event [Rhodes, Greece], September 12th to 14th, 2020 (Vol. 2663). CEUR-WS.org.

Borgwardt, S., Mailis, T., Peñaloza, R., &; Turhan, A.-Y. (2016). Answering Fuzzy Conjunctive Queries Over Finitely Valued Fuzzy Ontologies. Journal on Data Semantics, 5(2), 55–75.https://doi.org/10.1007/s13740-015-0055-y 

Carapelle, C., &; Turhan, A.-Y. (2016). Description Logics Reasoning w.r.t. General TBoxes is decidable for Concrete Domains with the EHD-property. Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016).https://doi.org/10.3233/978-1-61499-672-9-1440