[{"citation":{"ama":"Demir C, Yekini MO, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class Expression Learner over Large Graphs. In: <i>Lecture Notes in Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>","bibtex":"@inproceedings{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham}, title={Tree-Based OWL Class Expression Learner over Large Graphs}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Demir, Caglar and Yekini, Moshood Olawale and Röder, Michael and Mahmood, Yasir and Ngonga Ngomo, Axel-Cyrille}, year={2025} }","mla":"Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.” <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2025, doi:<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>.","chicago":"Demir, Caglar, Moshood Olawale Yekini, Michael Röder, Yasir Mahmood, and Axel-Cyrille Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large Graphs.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland, 2025. <a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">https://doi.org/10.1007/978-3-032-06066-2_29</a>.","short":"C. Demir, M.O. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.","apa":"Demir, C., Yekini, M. O., Röder, M., Mahmood, Y., &#38; Ngonga Ngomo, A.-C. (2025). Tree-Based OWL Class Expression Learner over Large Graphs. <i>Lecture Notes in Computer Science</i>. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto. <a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">https://doi.org/10.1007/978-3-032-06066-2_29</a>","ieee":"C. Demir, M. O. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based OWL Class Expression Learner over Large Graphs,” presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, 2025, doi: <a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>."},"publication":"Lecture Notes in Computer Science","department":[{"_id":"574"},{"_id":"923"}],"type":"conference","place":"Cham","date_created":"2026-01-12T17:13:22Z","date_updated":"2026-01-12T17:17:07Z","publication_status":"published","conference":{"end_date":"2025-09-19","start_date":"2025-09-15","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases","location":"Porto"},"publication_identifier":{"isbn":["9783032060655","9783032060662"],"issn":["0302-9743","1611-3349"]},"author":[{"last_name":"Demir","first_name":"Caglar","full_name":"Demir, Caglar","id":"43817"},{"id":"114533","full_name":"Yekini, Moshood Olawale","first_name":"Moshood Olawale","last_name":"Yekini"},{"id":"67199","full_name":"Röder, Michael","last_name":"Röder","first_name":"Michael","orcid":"https://orcid.org/0000-0002-8609-8277"},{"id":"99353","full_name":"Mahmood, Yasir","last_name":"Mahmood","first_name":"Yasir"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"}],"title":"Tree-Based OWL Class Expression Learner over Large Graphs","status":"public","year":"2025","doi":"10.1007/978-3-032-06066-2_29","user_id":"67199","_id":"63572","language":[{"iso":"eng"}],"publisher":"Springer Nature Switzerland"},{"date_updated":"2026-01-12T17:24:49Z","publication_status":"published","publication_identifier":{"isbn":["9783031945748","9783031945755"],"issn":["0302-9743","1611-3349"]},"author":[{"first_name":"Sourabh","last_name":"Kapoor","full_name":"Kapoor, Sourabh"},{"id":"67200","full_name":"Sharma, Arnab","last_name":"Sharma","first_name":"Arnab"},{"id":"67199","orcid":"https://orcid.org/0000-0002-8609-8277","first_name":"Michael","last_name":"Röder","full_name":"Röder, Michael"},{"id":"43817","full_name":"Demir, Caglar","first_name":"Caglar","last_name":"Demir"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","id":"65716"}],"title":"Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks","year":"2025","status":"public","doi":"10.1007/978-3-031-94575-5_15","user_id":"67199","_id":"63575","publisher":"Springer Nature Switzerland","language":[{"iso":"eng"}],"citation":{"bibtex":"@inproceedings{Kapoor_Sharma_Röder_Demir_Ngonga Ngomo_2025, place={Cham}, title={Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">10.1007/978-3-031-94575-5_15</a>}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Kapoor, Sourabh and Sharma, Arnab and Röder, Michael and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2025} }","ama":"Kapoor S, Sharma A, Röder M, Demir C, Ngonga Ngomo A-C. Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks. In: <i>Lecture Notes in Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">10.1007/978-3-031-94575-5_15</a>","mla":"Kapoor, Sourabh, et al. “Robustness Evaluation of Knowledge Graph Embedding Models Under Non-Targeted Attacks.” <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2025, doi:<a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">10.1007/978-3-031-94575-5_15</a>.","chicago":"Kapoor, Sourabh, Arnab Sharma, Michael Röder, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Robustness Evaluation of Knowledge Graph Embedding Models Under Non-Targeted Attacks.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland, 2025. <a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">https://doi.org/10.1007/978-3-031-94575-5_15</a>.","short":"S. Kapoor, A. Sharma, M. Röder, C. Demir, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.","ieee":"S. Kapoor, A. Sharma, M. Röder, C. Demir, and A.-C. Ngonga Ngomo, “Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks,” 2025, doi: <a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">10.1007/978-3-031-94575-5_15</a>.","apa":"Kapoor, S., Sharma, A., Röder, M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2025). Robustness Evaluation of Knowledge Graph Embedding Models Under Non-targeted Attacks. <i>Lecture Notes in Computer Science</i>. <a href=\"https://doi.org/10.1007/978-3-031-94575-5_15\">https://doi.org/10.1007/978-3-031-94575-5_15</a>"},"publication":"Lecture Notes in Computer Science","department":[{"_id":"574"},{"_id":"923"}],"type":"conference","place":"Cham","date_created":"2026-01-12T17:24:11Z"},{"doi":"10.1007/978-3-032-09527-5_6","user_id":"67199","publisher":"Springer Nature Switzerland","_id":"63573","language":[{"iso":"eng"}],"date_updated":"2026-01-12T17:24:46Z","publication_status":"published","status":"public","year":"2025","title":"Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?","author":[{"first_name":"Adel","last_name":"Memariani","full_name":"Memariani, Adel"},{"orcid":"https://orcid.org/0000-0002-8609-8277","last_name":"Röder","first_name":"Michael","full_name":"Röder, Michael","id":"67199"},{"id":"67200","full_name":"Sharma, Arnab","first_name":"Arnab","last_name":"Sharma"},{"id":"43817","full_name":"Demir, Caglar","last_name":"Demir","first_name":"Caglar"},{"id":"65716","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"publication_identifier":{"isbn":["9783032095268","9783032095275"],"issn":["0302-9743","1611-3349"]},"type":"conference","department":[{"_id":"574"},{"_id":"923"}],"place":"Cham","date_created":"2026-01-12T17:18:35Z","publication":"Lecture Notes in Computer Science","citation":{"mla":"Memariani, Adel, et al. “Link Prediction Under Non-Targeted Attacks: Do Soft Labels Always Help?” <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2025, doi:<a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">10.1007/978-3-032-09527-5_6</a>.","apa":"Memariani, A., Röder, M., Sharma, A., Demir, C., &#38; Ngonga Ngomo, A.-C. (2025). Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help? <i>Lecture Notes in Computer Science</i>. <a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">https://doi.org/10.1007/978-3-032-09527-5_6</a>","ieee":"A. Memariani, M. Röder, A. Sharma, C. Demir, and A.-C. Ngonga Ngomo, “Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?,” 2025, doi: <a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">10.1007/978-3-032-09527-5_6</a>.","ama":"Memariani A, Röder M, Sharma A, Demir C, Ngonga Ngomo A-C. Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help? In: <i>Lecture Notes in Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">10.1007/978-3-032-09527-5_6</a>","short":"A. Memariani, M. Röder, A. Sharma, C. Demir, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.","chicago":"Memariani, Adel, Michael Röder, Arnab Sharma, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Link Prediction Under Non-Targeted Attacks: Do Soft Labels Always Help?” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland, 2025. <a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">https://doi.org/10.1007/978-3-032-09527-5_6</a>.","bibtex":"@inproceedings{Memariani_Röder_Sharma_Demir_Ngonga Ngomo_2025, place={Cham}, title={Link Prediction Under Non-targeted Attacks: Do Soft Labels Always Help?}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-09527-5_6\">10.1007/978-3-032-09527-5_6</a>}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Memariani, Adel and Röder, Michael and Sharma, Arnab and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2025} }"}},{"date_created":"2026-05-29T14:12:43Z","department":[{"_id":"574"}],"oa":"1","type":"conference","citation":{"mla":"Kamdem Teyou, Louis Mozart, et al. <i>Neural Reasoning for Robust Instance Retrieval in SHOIQ</i>. 2025, doi:<a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>.","bibtex":"@inproceedings{Kamdem Teyou_Friedrichs_Kouagou_Demir_Mahmood_Heindorf_Ngonga Ngomo_2025, title={Neural Reasoning for Robust Instance Retrieval in SHOIQ}, DOI={<a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>}, author={Kamdem Teyou, Louis Mozart and Friedrichs, Luke and Kouagou, N’Dah Jean and Demir, Caglar and Mahmood, Yasir and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2025} }","ama":"Kamdem Teyou LM, Friedrichs L, Kouagou NJ, et al. Neural Reasoning for Robust Instance Retrieval in SHOIQ. In: ; 2025. doi:<a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>","ieee":"L. M. Kamdem Teyou <i>et al.</i>, “Neural Reasoning for Robust Instance Retrieval in SHOIQ,” presented at the The 13th COnference on Knowledge Capture (K-CAP’25), Dayton-USA, 2025, doi: <a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>.","apa":"Kamdem Teyou, L. M., Friedrichs, L., Kouagou, N. J., Demir, C., Mahmood, Y., Heindorf, S., &#38; Ngonga Ngomo, A.-C. (2025). <i>Neural Reasoning for Robust Instance Retrieval in SHOIQ</i>. The 13th COnference on Knowledge Capture (K-CAP’25), Dayton-USA. <a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>","short":"L.M. Kamdem Teyou, L. Friedrichs, N.J. Kouagou, C. Demir, Y. Mahmood, S. Heindorf, A.-C. Ngonga Ngomo, in: 2025.","chicago":"Kamdem Teyou, Louis Mozart, Luke Friedrichs, N’Dah Jean Kouagou, Caglar Demir, Yasir Mahmood, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo. “Neural Reasoning for Robust Instance Retrieval in SHOIQ,” 2025. <a href=\"https://doi.org/10.1145/3731443.377134\">https://doi.org/10.1145/3731443.377134</a>."},"language":[{"iso":"eng"}],"_id":"65734","main_file_link":[{"open_access":"1","url":"https://dl.acm.org/doi/10.1145/3731443.3771348"}],"user_id":"101165","doi":"https://doi.org/10.1145/3731443.377134","author":[{"full_name":"Kamdem Teyou, Louis Mozart","first_name":"Louis Mozart","last_name":"Kamdem Teyou","id":"101165"},{"last_name":"Friedrichs","first_name":"Luke","full_name":"Friedrichs, Luke"},{"id":"87189","full_name":"Kouagou, N'Dah Jean","first_name":"N'Dah Jean","last_name":"Kouagou"},{"id":"43817","first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar"},{"id":"99353","first_name":"Yasir","last_name":"Mahmood","full_name":"Mahmood, Yasir"},{"full_name":"Heindorf, Stefan","first_name":"Stefan","last_name":"Heindorf","orcid":"0000-0002-4525-6865","id":"11871"},{"id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo"}],"conference":{"end_date":"2025-12-12","name":"The 13th COnference on Knowledge Capture (K-CAP'25)","start_date":"2025-12-09","location":"Dayton-USA"},"year":"2025","title":"Neural Reasoning for Robust Instance Retrieval in SHOIQ","status":"public","date_updated":"2026-05-29T14:16:06Z"},{"main_file_link":[{"open_access":"1","url":"https://dl.acm.org/doi/abs/10.1145/3589335.3651978"}],"_id":"54449","publisher":"ACM","language":[{"iso":"eng"}],"user_id":"11871","doi":"10.1145/3589335.3651978","year":"2024","title":"Universal Knowledge Graph Embeddings","status":"public","author":[{"full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean","last_name":"KOUAGOU","id":"87189"},{"full_name":"Demir, Caglar","first_name":"Caglar","last_name":"Demir","id":"43817"},{"id":"72768","orcid":"0000-0003-0215-1278","first_name":"Hamada Mohamed Abdelsamee","last_name":"Zahera","full_name":"Zahera, Hamada Mohamed Abdelsamee"},{"last_name":"Wilke","orcid":"0000-0002-6575-807X","first_name":"Adrian","full_name":"Wilke, Adrian","id":"9101"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","first_name":"Stefan","full_name":"Heindorf, Stefan"},{"first_name":"Jiayi","last_name":"Li","full_name":"Li, Jiayi"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"}],"conference":{"end_date":"2024-05-17","name":"Companion Proceedings of the ACM on Web Conference 2024","start_date":"2024-05-13","location":"Singapore"},"publication_status":"published","date_updated":"2024-05-26T19:06:10Z","date_created":"2024-05-26T18:52:47Z","type":"conference","department":[{"_id":"760"},{"_id":"574"}],"oa":"1","publication":"Companion Proceedings of the ACM on Web Conference 2024","citation":{"ama":"KOUAGOU NJ, Demir C, Zahera HMA, et al. Universal Knowledge Graph Embeddings. In: <i>Companion Proceedings of the ACM on Web Conference 2024</i>. ACM; 2024. doi:<a href=\"https://doi.org/10.1145/3589335.3651978\">10.1145/3589335.3651978</a>","bibtex":"@inproceedings{KOUAGOU_Demir_Zahera_Wilke_Heindorf_Li_Ngonga Ngomo_2024, title={Universal Knowledge Graph Embeddings}, DOI={<a href=\"https://doi.org/10.1145/3589335.3651978\">10.1145/3589335.3651978</a>}, booktitle={Companion Proceedings of the ACM on Web Conference 2024}, publisher={ACM}, author={KOUAGOU, N’Dah Jean and Demir, Caglar and Zahera, Hamada Mohamed Abdelsamee and Wilke, Adrian and Heindorf, Stefan and Li, Jiayi and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","mla":"KOUAGOU, N’Dah Jean, et al. “Universal Knowledge Graph Embeddings.” <i>Companion Proceedings of the ACM on Web Conference 2024</i>, ACM, 2024, doi:<a href=\"https://doi.org/10.1145/3589335.3651978\">10.1145/3589335.3651978</a>.","chicago":"KOUAGOU, N’Dah Jean, Caglar Demir, Hamada Mohamed Abdelsamee Zahera, Adrian Wilke, Stefan Heindorf, Jiayi Li, and Axel-Cyrille Ngonga Ngomo. “Universal Knowledge Graph Embeddings.” In <i>Companion Proceedings of the ACM on Web Conference 2024</i>. ACM, 2024. <a href=\"https://doi.org/10.1145/3589335.3651978\">https://doi.org/10.1145/3589335.3651978</a>.","short":"N.J. KOUAGOU, C. Demir, H.M.A. Zahera, A. Wilke, S. Heindorf, J. Li, A.-C. Ngonga Ngomo, in: Companion Proceedings of the ACM on Web Conference 2024, ACM, 2024.","apa":"KOUAGOU, N. J., Demir, C., Zahera, H. M. A., Wilke, A., Heindorf, S., Li, J., &#38; Ngonga Ngomo, A.-C. (2024). Universal Knowledge Graph Embeddings. <i>Companion Proceedings of the ACM on Web Conference 2024</i>. Companion Proceedings of the ACM on Web Conference 2024, Singapore. <a href=\"https://doi.org/10.1145/3589335.3651978\">https://doi.org/10.1145/3589335.3651978</a>","ieee":"N. J. KOUAGOU <i>et al.</i>, “Universal Knowledge Graph Embeddings,” presented at the Companion Proceedings of the ACM on Web Conference 2024, Singapore, 2024, doi: <a href=\"https://doi.org/10.1145/3589335.3651978\">10.1145/3589335.3651978</a>."}},{"abstract":[{"lang":"eng","text":"In recent years, knowledge graph embedding models have been successfully applied in the transductive setting to tackle various challenging tasks including link prediction, and query answering. Yet, the transductive setting does not allow for reasoning over unseen entities, relations, let alone numerical or non-numerical literals. Although increasing efforts are put into exploring inductive scenarios, inference over unseen entities, relations, and literals has yet to come. This limitation prohibits the existing methods from handling real-world dynamic knowledge graphs involving heterogeneous information about the world. Here, we propose a remedy to this limitation. We propose the attentive byte-pair encoding layer (BytE) to construct a triple embedding from a sequence of byte-pair encoded subword units of entities and relations. Compared to the conventional setting, BytE leads to massive feature reuse via weight tying, since it forces a knowledge graph embedding model to learn embeddings for subword units instead of entities and relations directly. Consequently, the size of the embedding matrices are not anymore bound to the unique number of entities and relations of a knowledge graph. Experimental results show that BytE improves the link prediction performance of 4 knowledge graph embedding models on datasets where the syntactic representations of triples are semantically meaningful. However, benefits of training a knowledge graph embedding model with BytE dissipate on knowledge graphs where entities and relations are represented with plain numbers or URIs. We provide an open source implementation of BytE to foster reproducible research."}],"citation":{"short":"C. Demir, N.J. KOUAGOU, A. Sharma, A.-C. Ngonga Ngomo, Arxiv (2024).","chicago":"Demir, Caglar, N’Dah Jean KOUAGOU, Arnab Sharma, and Axel-Cyrille Ngonga Ngomo. “Inference over Unseen Entities, Relations and Literals on Knowledge Graphs.” <i>Arxiv</i>, 2024. <a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">https://doi.org/10.48550/ARXIV.2410.06742</a>.","apa":"Demir, C., KOUAGOU, N. J., Sharma, A., &#38; Ngonga Ngomo, A.-C. (2024). Inference over Unseen Entities, Relations and Literals on Knowledge Graphs. <i>Arxiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">https://doi.org/10.48550/ARXIV.2410.06742</a>","ieee":"C. Demir, N. J. KOUAGOU, A. Sharma, and A.-C. Ngonga Ngomo, “Inference over Unseen Entities, Relations and Literals on Knowledge Graphs,” <i>Arxiv</i>, 2024, doi: <a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">10.48550/ARXIV.2410.06742</a>.","ama":"Demir C, KOUAGOU NJ, Sharma A, Ngonga Ngomo A-C. Inference over Unseen Entities, Relations and Literals on Knowledge Graphs. <i>Arxiv</i>. Published online 2024. doi:<a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">10.48550/ARXIV.2410.06742</a>","bibtex":"@article{Demir_KOUAGOU_Sharma_Ngonga Ngomo_2024, title={Inference over Unseen Entities, Relations and Literals on Knowledge Graphs}, DOI={<a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">10.48550/ARXIV.2410.06742</a>}, journal={Arxiv}, author={Demir, Caglar and KOUAGOU, N’Dah Jean and Sharma, Arnab and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","mla":"Demir, Caglar, et al. “Inference over Unseen Entities, Relations and Literals on Knowledge Graphs.” <i>Arxiv</i>, 2024, doi:<a href=\"https://doi.org/10.48550/ARXIV.2410.06742\">10.48550/ARXIV.2410.06742</a>."},"publication":"Arxiv","type":"journal_article","date_created":"2025-01-06T12:19:39Z","date_updated":"2025-01-07T20:01:36Z","author":[{"last_name":"Demir","first_name":"Caglar","full_name":"Demir, Caglar","id":"43817"},{"id":"87189","last_name":"KOUAGOU","first_name":"N'Dah Jean","full_name":"KOUAGOU, N'Dah Jean"},{"id":"67200","full_name":"Sharma, Arnab","last_name":"Sharma","first_name":"Arnab"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"}],"status":"public","title":"Inference over Unseen Entities, Relations and Literals on Knowledge Graphs","year":"2024","doi":"10.48550/ARXIV.2410.06742","user_id":"67200","language":[{"iso":"eng"}],"_id":"58049"},{"type":"journal_article","date_created":"2025-01-06T12:20:24Z","publication":"arxiv","citation":{"mla":"Demir, Caglar, et al. “Adaptive Stochastic Weight Averaging.” <i>Arxiv</i>, 2024, doi:<a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">10.48550/ARXIV.2406.19092</a>.","ama":"Demir C, Sharma A, Ngonga Ngomo A-C. Adaptive Stochastic Weight Averaging. <i>arxiv</i>. Published online 2024. doi:<a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">10.48550/ARXIV.2406.19092</a>","bibtex":"@article{Demir_Sharma_Ngonga Ngomo_2024, title={Adaptive Stochastic Weight Averaging}, DOI={<a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">10.48550/ARXIV.2406.19092</a>}, journal={arxiv}, author={Demir, Caglar and Sharma, Arnab and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","apa":"Demir, C., Sharma, A., &#38; Ngonga Ngomo, A.-C. (2024). Adaptive Stochastic Weight Averaging. <i>Arxiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">https://doi.org/10.48550/ARXIV.2406.19092</a>","ieee":"C. Demir, A. Sharma, and A.-C. Ngonga Ngomo, “Adaptive Stochastic Weight Averaging,” <i>arxiv</i>, 2024, doi: <a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">10.48550/ARXIV.2406.19092</a>.","short":"C. Demir, A. Sharma, A.-C. Ngonga Ngomo, Arxiv (2024).","chicago":"Demir, Caglar, Arnab Sharma, and Axel-Cyrille Ngonga Ngomo. “Adaptive Stochastic Weight Averaging.” <i>Arxiv</i>, 2024. <a href=\"https://doi.org/10.48550/ARXIV.2406.19092\">https://doi.org/10.48550/ARXIV.2406.19092</a>."},"user_id":"67200","doi":"10.48550/ARXIV.2406.19092","_id":"58051","language":[{"iso":"eng"}],"date_updated":"2025-01-07T20:00:53Z","status":"public","year":"2024","title":"Adaptive Stochastic Weight Averaging","author":[{"first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar","id":"43817"},{"id":"67200","first_name":"Arnab","last_name":"Sharma","full_name":"Sharma, Arnab"},{"id":"65716","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}]},{"has_accepted_license":"1","date_updated":"2025-07-18T15:52:39Z","publication_status":"published","author":[{"full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean","last_name":"KOUAGOU","id":"87189"},{"orcid":"0000-0002-4525-6865","last_name":"Heindorf","first_name":"Stefan","full_name":"Heindorf, Stefan","id":"11871"},{"id":"43817","full_name":"Demir, Caglar","last_name":"Demir","first_name":"Caglar"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"}],"title":"ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling","status":"public","year":"2024","doi":"10.24963/ijcai.2024/479","ddc":["000"],"user_id":"11871","_id":"55653","publisher":"International Joint Conferences on Artificial Intelligence Organization","language":[{"iso":"eng"}],"abstract":[{"text":"We consider the problem of class expression learning using cardinality-minimal sets of examples. Recent class expression learning approaches employ deep neural networks and have demonstrated tremendous performance improvements in execution time and quality of the computed solutions. However, they lack generalization capabilities when it comes to the number of examples used in a learning problem, i.e., they often perform poorly on unseen learning problems where only a few examples are given. In this work, we propose a generalization of the classical class expression learning problem to address the limitations above. In short, our generalized learning problem (GLP) forces learning systems to solve the classical class expression learning problem using the smallest possible subsets of examples, thereby improving the learning systems' ability to solve unseen learning problems with arbitrary numbers of examples. Moreover, we develop ROCES, a learning algorithm for synthesis-based approaches to solve GLP. Experimental results suggest that post training, ROCES outperforms existing synthesis-based approaches on out-of-distribution learning problems while remaining highly competitive overall.","lang":"eng"}],"citation":{"short":"N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, 2024.","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling.” In <i>Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence</i>. International Joint Conferences on Artificial Intelligence Organization, 2024. <a href=\"https://doi.org/10.24963/ijcai.2024/479\">https://doi.org/10.24963/ijcai.2024/479</a>.","ieee":"N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling,” 2024, doi: <a href=\"https://doi.org/10.24963/ijcai.2024/479\">10.24963/ijcai.2024/479</a>.","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024). ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling. <i>Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence</i>. <a href=\"https://doi.org/10.24963/ijcai.2024/479\">https://doi.org/10.24963/ijcai.2024/479</a>","bibtex":"@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2024, title={ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling}, DOI={<a href=\"https://doi.org/10.24963/ijcai.2024/479\">10.24963/ijcai.2024/479</a>}, booktitle={Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence}, publisher={International Joint Conferences on Artificial Intelligence Organization}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","ama":"KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling. In: <i>Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence</i>. International Joint Conferences on Artificial Intelligence Organization; 2024. doi:<a href=\"https://doi.org/10.24963/ijcai.2024/479\">10.24963/ijcai.2024/479</a>","mla":"KOUAGOU, N’Dah Jean, et al. “ROCES: Robust Class Expression Synthesis in Description Logics via Iterative Sampling.” <i>Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence</i>, International Joint Conferences on Artificial Intelligence Organization, 2024, doi:<a href=\"https://doi.org/10.24963/ijcai.2024/479\">10.24963/ijcai.2024/479</a>."},"publication":"Proceedings of the Thirty-ThirdInternational Joint Conference on Artificial Intelligence","file_date_updated":"2025-06-26T08:06:07Z","type":"conference","date_created":"2024-08-19T12:43:55Z","file":[{"file_id":"60394","success":1,"content_type":"application/pdf","relation":"main_file","date_updated":"2025-06-26T08:06:07Z","file_name":"public.pdf","access_level":"closed","file_size":400277,"date_created":"2025-06-26T08:06:07Z","creator":"nkouagou"}]},{"citation":{"ama":"Kamdem Teyou LM, Demir C, Ngonga Ngomo A-C. Embedding Knowledge Graphs in Degenerate Clifford Algebras. In: <i>Frontiers in Artificial Intelligence and Applications</i>. IOS Press; 2024. doi:<a href=\"https://doi.org/10.3233/faia240627\">10.3233/faia240627</a>","bibtex":"@inbook{Kamdem Teyou_Demir_Ngonga Ngomo_2024, title={Embedding Knowledge Graphs in Degenerate Clifford Algebras}, DOI={<a href=\"https://doi.org/10.3233/faia240627\">10.3233/faia240627</a>}, booktitle={Frontiers in Artificial Intelligence and Applications}, publisher={IOS Press}, author={Kamdem Teyou, Louis Mozart and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","mla":"Kamdem Teyou, Louis Mozart, et al. “Embedding Knowledge Graphs in Degenerate Clifford Algebras.” <i>Frontiers in Artificial Intelligence and Applications</i>, IOS Press, 2024, doi:<a href=\"https://doi.org/10.3233/faia240627\">10.3233/faia240627</a>.","short":"L.M. Kamdem Teyou, C. Demir, A.-C. Ngonga Ngomo, in: Frontiers in Artificial Intelligence and Applications, IOS Press, 2024.","chicago":"Kamdem Teyou, Louis Mozart, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Embedding Knowledge Graphs in Degenerate Clifford Algebras.” In <i>Frontiers in Artificial Intelligence and Applications</i>. IOS Press, 2024. <a href=\"https://doi.org/10.3233/faia240627\">https://doi.org/10.3233/faia240627</a>.","apa":"Kamdem Teyou, L. M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024). Embedding Knowledge Graphs in Degenerate Clifford Algebras. In <i>Frontiers in Artificial Intelligence and Applications</i>. 27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE, Santiago de Compostela. IOS Press. <a href=\"https://doi.org/10.3233/faia240627\">https://doi.org/10.3233/faia240627</a>","ieee":"L. M. Kamdem Teyou, C. Demir, and A.-C. Ngonga Ngomo, “Embedding Knowledge Graphs in Degenerate Clifford Algebras,” in <i>Frontiers in Artificial Intelligence and Applications</i>, IOS Press, 2024."},"popular_science":"1","quality_controlled":"1","_id":"62702","publisher":"IOS Press","user_id":"101165","conference":{"end_date":"2024-10-24","name":"27TH EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE","start_date":"2024-10-19","location":"Santiago de Compostela"},"status":"public","date_created":"2025-11-28T14:32:43Z","department":[{"_id":"34"},{"_id":"574"}],"type":"book_chapter","publication":"Frontiers in Artificial Intelligence and Applications","abstract":[{"lang":"eng","text":"<jats:p>Clifford algebras are a natural extension of division algebras, including real numbers, complex numbers, quaternions, and octonions. Previous research in knowledge graph embeddings has focused exclusively on Clifford algebras of a specific type, which do not include nilpotent base vectors—elements that square to zero. In this work, we introduce a novel approach by incorporating nilpotent base vectors with a nilpotency index of two, leading to a more general form of Clifford algebras named degenerate Clifford algebras. This generalization to degenerate Clifford algebras does allow for covering dual numbers and as such include translations and rotations models under the same generalization paradigm for the first time. We develop two models to determine the parameters that define the algebra: one using a greedy search and another predicting the parameters based on neural network embeddings of the input knowledge graph. Our evaluation on seven benchmark datasets demonstrates that this incorporation of nilpotent vectors enhances the quality of embeddings. Additionally, our method outperforms state-of-the-art approaches in terms of generalization, particularly regarding the mean reciprocal rank achieved on validation data. Finally, we show that even a simple greedy search can effectively discover optimal or near-optimal parameters for the algebra.</jats:p>"}],"language":[{"iso":"eng"}],"doi":"10.3233/faia240627","author":[{"last_name":"Kamdem Teyou","first_name":"Louis Mozart","full_name":"Kamdem Teyou, Louis Mozart","id":"101165"},{"last_name":"Demir","first_name":"Caglar","full_name":"Demir, Caglar","id":"43817"},{"id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo"}],"publication_identifier":{"isbn":["9781643685489"],"issn":["0922-6389","1879-8314"]},"title":"Embedding Knowledge Graphs in Degenerate Clifford Algebras","year":"2024","publication_status":"published","date_updated":"2026-05-29T14:34:11Z"},{"language":[{"iso":"eng"}],"_id":"62703","publisher":"ACM","user_id":"101165","doi":"10.1145/3627673.3679819","author":[{"id":"101165","first_name":"Louis Mozart","last_name":"Kamdem Teyou","full_name":"Kamdem Teyou, Louis Mozart"},{"id":"43817","first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"conference":{"end_date":"2024-10-25","name":"33rd ACM International Conference on Information and Knowledge Management","start_date":"2024-10-21","location":"Boise"},"title":"Embedding Knowledge Graphs in Function Spaces","year":"2024","status":"public","publication_status":"published","date_updated":"2026-05-29T14:32:04Z","date_created":"2025-11-28T14:42:32Z","place":"Boise","department":[{"_id":"34"},{"_id":"574"}],"type":"conference","citation":{"mla":"Kamdem Teyou, Louis Mozart, et al. “Embedding Knowledge Graphs in Function Spaces.” <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>, ACM, 2024, doi:<a href=\"https://doi.org/10.1145/3627673.3679819\">10.1145/3627673.3679819</a>.","bibtex":"@inproceedings{Kamdem Teyou_Demir_Ngonga Ngomo_2024, place={Boise}, title={Embedding Knowledge Graphs in Function Spaces}, DOI={<a href=\"https://doi.org/10.1145/3627673.3679819\">10.1145/3627673.3679819</a>}, booktitle={Proceedings of the 33rd ACM International Conference on Information and Knowledge Management}, publisher={ACM}, author={Kamdem Teyou, Louis Mozart and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2024} }","ama":"Kamdem Teyou LM, Demir C, Ngonga Ngomo A-C. Embedding Knowledge Graphs in Function Spaces. In: <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>. ACM; 2024. doi:<a href=\"https://doi.org/10.1145/3627673.3679819\">10.1145/3627673.3679819</a>","ieee":"L. M. Kamdem Teyou, C. Demir, and A.-C. Ngonga Ngomo, “Embedding Knowledge Graphs in Function Spaces,” presented at the 33rd ACM International Conference on Information and Knowledge Management, Boise, 2024, doi: <a href=\"https://doi.org/10.1145/3627673.3679819\">10.1145/3627673.3679819</a>.","apa":"Kamdem Teyou, L. M., Demir, C., &#38; Ngonga Ngomo, A.-C. (2024). Embedding Knowledge Graphs in Function Spaces. <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>. 33rd ACM International Conference on Information and Knowledge Management, Boise. <a href=\"https://doi.org/10.1145/3627673.3679819\">https://doi.org/10.1145/3627673.3679819</a>","chicago":"Kamdem Teyou, Louis Mozart, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Embedding Knowledge Graphs in Function Spaces.” In <i>Proceedings of the 33rd ACM International Conference on Information and Knowledge Management</i>. Boise: ACM, 2024. <a href=\"https://doi.org/10.1145/3627673.3679819\">https://doi.org/10.1145/3627673.3679819</a>.","short":"L.M. Kamdem Teyou, C. Demir, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, ACM, Boise, 2024."},"publication":"Proceedings of the 33rd ACM International Conference on Information and Knowledge Management","abstract":[{"lang":"eng","text":"We introduce a novel embedding method diverging from conventional approaches by operating within function spaces of finite dimension rather than finite vector space, thus departing significantly from standard knowledge graph embedding techniques. Initially employing polynomial functions to compute embeddings, we progress to more intricate representations using neural networks with varying layer complexities. We argue that employing functions for embedding computation enhances expressiveness and allows for more degrees of freedom, enabling operations such as composition, derivatives and primitive of entities representation. Additionally, we meticulously outline the step-by-step construction of our approach and provide code for reproducibility, thereby facilitating further exploration and application in the field."}]},{"language":[{"iso":"eng"}],"_id":"46460","publisher":"IOS Press","page":"272–286","user_id":"14931","author":[{"id":"65716","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"},{"full_name":"Demir, Caglar","first_name":"Caglar","last_name":"Demir","id":"43817"},{"id":"87189","full_name":"Kouagou, N'Dah Jean","last_name":"Kouagou","first_name":"N'Dah Jean"},{"orcid":"0000-0002-4525-6865","last_name":"Heindorf","first_name":"Stefan","full_name":"Heindorf, Stefan","id":"11871"},{"first_name":"Nikoloas","last_name":"Karalis","full_name":"Karalis, Nikoloas"},{"first_name":"Alexander","last_name":"Bigerl","full_name":"Bigerl, Alexander","id":"72857"}],"year":"2023","title":"Class Expression Learning with Multiple Representations","status":"public","date_updated":"2023-11-21T08:06:20Z","date_created":"2023-08-08T11:49:51Z","department":[{"_id":"760"},{"_id":"574"}],"type":"book_chapter","citation":{"mla":"Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple Representations.” <i>Compendium of Neurosymbolic Artificial Intelligence</i>, IOS Press, 2023, pp. 272–286.","ama":"Ngonga Ngomo A-C, Demir C, Kouagou NJ, Heindorf S, Karalis N, Bigerl A. Class Expression Learning with Multiple Representations. In: <i>Compendium of Neurosymbolic Artificial Intelligence</i>. IOS Press; 2023:272–286.","bibtex":"@inbook{Ngonga Ngomo_Demir_Kouagou_Heindorf_Karalis_Bigerl_2023, title={Class Expression Learning with Multiple Representations}, booktitle={Compendium of Neurosymbolic Artificial Intelligence}, publisher={IOS Press}, author={Ngonga Ngomo, Axel-Cyrille and Demir, Caglar and Kouagou, N’Dah Jean and Heindorf, Stefan and Karalis, Nikoloas and Bigerl, Alexander}, year={2023}, pages={272–286} }","apa":"Ngonga Ngomo, A.-C., Demir, C., Kouagou, N. J., Heindorf, S., Karalis, N., &#38; Bigerl, A. (2023). Class Expression Learning with Multiple Representations. In <i>Compendium of Neurosymbolic Artificial Intelligence</i> (pp. 272–286). IOS Press.","ieee":"A.-C. Ngonga Ngomo, C. Demir, N. J. Kouagou, S. Heindorf, N. Karalis, and A. Bigerl, “Class Expression Learning with Multiple Representations,” in <i>Compendium of Neurosymbolic Artificial Intelligence</i>, IOS Press, 2023, pp. 272–286.","chicago":"Ngonga Ngomo, Axel-Cyrille, Caglar Demir, N’Dah Jean Kouagou, Stefan Heindorf, Nikoloas Karalis, and Alexander Bigerl. “Class Expression Learning with Multiple Representations.” In <i>Compendium of Neurosymbolic Artificial Intelligence</i>, 272–286. IOS Press, 2023.","short":"A.-C. Ngonga Ngomo, C. Demir, N.J. Kouagou, S. Heindorf, N. Karalis, A. Bigerl, in: Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286."},"publication":"Compendium of Neurosymbolic Artificial Intelligence"},{"project":[{"grant_number":"101070305","_id":"407","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs"},{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410","grant_number":"860801"},{"grant_number":"NW21-059D","_id":"285","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems"}],"citation":{"mla":"Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals.” <i>ECML PKDD</i>, 2023.","bibtex":"@article{Demir_Wiebesiek_Lu_Ngonga Ngomo_Heindorf_2023, title={LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals}, journal={ECML PKDD}, author={Demir, Caglar and Wiebesiek, Michel and Lu, Renzhong and Ngonga Ngomo, Axel-Cyrille and Heindorf, Stefan}, year={2023} }","ama":"Demir C, Wiebesiek M, Lu R, Ngonga Ngomo A-C, Heindorf S. LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals. <i>ECML PKDD</i>. Published online 2023.","ieee":"C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, and S. Heindorf, “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals,” <i>ECML PKDD</i>, 2023.","apa":"Demir, C., Wiebesiek, M., Lu, R., Ngonga Ngomo, A.-C., &#38; Heindorf, S. (2023). LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals. <i>ECML PKDD</i>. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Torino.","chicago":"Demir, Caglar, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo, and Stefan Heindorf. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals.” <i>ECML PKDD</i>, 2023.","short":"C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (2023)."},"file_date_updated":"2023-08-01T09:24:15Z","publication":"ECML PKDD","department":[{"_id":"574"},{"_id":"760"}],"oa":"1","type":"journal_article","date_created":"2023-08-01T09:24:21Z","file":[{"file_id":"46249","content_type":"application/pdf","relation":"main_file","date_updated":"2023-08-01T09:24:15Z","file_name":"public.pdf","access_level":"open_access","file_size":562759,"date_created":"2023-08-01T09:24:15Z","creator":"cdemir"}],"has_accepted_license":"1","date_updated":"2024-03-06T16:18:53Z","author":[{"first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar","id":"43817"},{"last_name":"Wiebesiek","first_name":"Michel","full_name":"Wiebesiek, Michel"},{"full_name":"Lu, Renzhong","first_name":"Renzhong","last_name":"Lu"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"},{"full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","first_name":"Stefan","id":"11871"}],"conference":{"location":"Torino","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases"},"year":"2023","status":"public","title":"LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals","user_id":"14931","ddc":["000"],"language":[{"iso":"eng"}],"_id":"46248"},{"conference":{"location":"Turin","start_date":"2023-09-18","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases","end_date":"2023-09-22"},"status":"public","has_accepted_license":"1","publisher":"Springer Nature Switzerland","_id":"47421","user_id":"11871","ddc":["000"],"citation":{"ieee":"N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis in ALCHIQ(D),” in <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>, Cham: Springer Nature Switzerland, 2023.","apa":"Kouagou, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis in ALCHIQ(D). In <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-031-43421-1_12\">https://doi.org/10.1007/978-3-031-43421-1_12</a>","short":"N.J. Kouagou, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, Cham, 2023.","chicago":"Kouagou, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis in ALCHIQ(D).” In <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>. Cham: Springer Nature Switzerland, 2023. <a href=\"https://doi.org/10.1007/978-3-031-43421-1_12\">https://doi.org/10.1007/978-3-031-43421-1_12</a>.","mla":"Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).” <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>, Springer Nature Switzerland, 2023, doi:<a href=\"https://doi.org/10.1007/978-3-031-43421-1_12\">10.1007/978-3-031-43421-1_12</a>.","bibtex":"@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural Class Expression Synthesis in ALCHIQ(D)}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-43421-1_12\">10.1007/978-3-031-43421-1_12</a>}, booktitle={Machine Learning and Knowledge Discovery in Databases: Research Track}, publisher={Springer Nature Switzerland}, author={Kouagou, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","ama":"Kouagou NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis in ALCHIQ(D). In: <i>Machine Learning and Knowledge Discovery in Databases: Research Track</i>. Springer Nature Switzerland; 2023. doi:<a href=\"https://doi.org/10.1007/978-3-031-43421-1_12\">10.1007/978-3-031-43421-1_12</a>"},"file_date_updated":"2024-05-22T10:46:58Z","place":"Cham","oa":"1","author":[{"id":"87189","full_name":"Kouagou, N'Dah Jean","last_name":"Kouagou","first_name":"N'Dah Jean"},{"id":"11871","last_name":"Heindorf","first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan"},{"id":"43817","first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar"},{"id":"65716","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"publication_identifier":{"isbn":["9783031434204","9783031434211"],"issn":["0302-9743","1611-3349"]},"year":"2023","title":"Neural Class Expression Synthesis in ALCHIQ(D)","publication_status":"published","date_updated":"2024-05-22T10:48:24Z","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://papers.dice-research.org/2023/ECML_NCES2/NCES2_public.pdf"}],"doi":"10.1007/978-3-031-43421-1_12","publication":"Machine Learning and Knowledge Discovery in Databases: Research Track","abstract":[{"text":"Class expression learning in description logics has long been regarded as an iterative search problem in an infinite conceptual space. Each iteration of the search process invokes a reasoner and a heuristic function. The reasoner finds the instances of the current expression, and the heuristic function computes the information gain and decides on the next step to be taken. As the size of the background knowledge base grows, search-based approaches for class expression learning become prohibitively slow. Current neural class expression synthesis (NCES) approaches investigate the use of neural networks for class expression learning in the attributive language with complement (ALC). While they show significant improvements over search-based approaches in runtime and quality of the computed solutions, they rely on the availability of pretrained embeddings for the input knowledge base. Moreover, they are not applicable to ontologies in more expressive description logics. In this paper, we propose a novel NCES approach which extends the state of the art to the description logic ALCHIQ(D). Our extension, dubbed NCES2, comes with an improved training data generator and does not require pretrained embeddings for the input knowledge base as both the embedding model and the class expression synthesizer are trained jointly. Empirical results on benchmark datasets suggest that our approach inherits the scalability capability of current NCES instances with the additional advantage that it supports more complex learning problems. NCES2 achieves the highest performance overall when compared to search-based approaches and to its predecessor NCES. We provide our source code, datasets, and pretrained models at https://github.com/dice-group/NCES2.","lang":"eng"}],"date_created":"2023-09-25T13:42:01Z","file":[{"creator":"heindorf","date_created":"2024-05-22T10:45:08Z","date_updated":"2024-05-22T10:46:58Z","relation":"main_file","file_size":432708,"access_level":"open_access","file_name":"NCES2_public.pdf","content_type":"application/pdf","file_id":"54417"}],"department":[{"_id":"760"},{"_id":"574"}],"type":"book_chapter"},{"user_id":"67199","_id":"54612","publisher":"CEUR-WS","language":[{"iso":"eng"}],"date_updated":"2024-06-04T15:40:30Z","year":"2023","status":"public","title":"Neural Class Expression Synthesis (Extended Abstract)","author":[{"id":"87189","last_name":"KOUAGOU","first_name":"N'Dah Jean","full_name":"KOUAGOU, N'Dah Jean"},{"id":"11871","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","first_name":"Stefan","last_name":"Heindorf"},{"full_name":"Demir, Caglar","last_name":"Demir","first_name":"Caglar","id":"43817"},{"id":"65716","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"type":"conference","keyword":["318 SFB-TRR demir dice enexa heindorf knowgraphs kouagou ngonga sail"],"department":[{"_id":"574"},{"_id":"760"}],"date_created":"2024-06-04T15:36:52Z","publication":"NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa di Pontignano, Siena, Italy","citation":{"mla":"KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis (Extended Abstract).” <i>NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy</i>, CEUR-WS, 2023.","ama":"KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis (Extended Abstract). In: <i>NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy</i>. CEUR-WS; 2023.","bibtex":"@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis (Extended Abstract)}, booktitle={NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa di Pontignano, Siena, Italy}, publisher={CEUR-WS}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis (Extended Abstract). <i>NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy</i>.","ieee":"N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis (Extended Abstract),” 2023.","short":"N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy, CEUR-WS, 2023.","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis (Extended Abstract).” In <i>NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, Certosa Di Pontignano, Siena, Italy</i>. CEUR-WS, 2023."}},{"department":[{"_id":"574"}],"type":"conference","keyword":["318 SFB-TRR demir dice enexa ngonga sail"],"date_created":"2024-06-04T15:58:48Z","citation":{"ieee":"C. Demir and A.-C. Ngonga Ngomo, “Learning Permutation-Invariant Embeddings for Description Logic Concepts,” in <i>Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings</i>, 2023, pp. 103–115.","apa":"Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Learning Permutation-Invariant Embeddings for Description Logic Concepts. <i>Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings</i>, 103–115.","short":"C. Demir, A.-C. Ngonga Ngomo, in: Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings, 2023, pp. 103–115.","chicago":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Learning Permutation-Invariant Embeddings for Description Logic Concepts.” In <i>Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings</i>, 103–115, 2023.","mla":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Learning Permutation-Invariant Embeddings for Description Logic Concepts.” <i>Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings</i>, 2023, pp. 103–115.","bibtex":"@inproceedings{Demir_Ngonga Ngomo_2023, title={Learning Permutation-Invariant Embeddings for Description Logic Concepts}, booktitle={Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings}, author={Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023}, pages={103–115} }","ama":"Demir C, Ngonga Ngomo A-C. Learning Permutation-Invariant Embeddings for Description Logic Concepts. In: <i>Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-La-Neuve, Belgium, April 12–14, 2023, Proceedings</i>. ; 2023:103–115."},"publication":"Advances in Intelligent Data Analysis XXI: 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings","user_id":"67199","language":[{"iso":"eng"}],"_id":"54615","page":"103–115","date_updated":"2024-06-04T15:59:04Z","author":[{"full_name":"Demir, Caglar","first_name":"Caglar","last_name":"Demir","id":"43817"},{"id":"65716","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"status":"public","title":"Learning Permutation-Invariant Embeddings for Description Logic Concepts","year":"2023"},{"abstract":[{"text":"Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis","lang":"eng"}],"publication":"The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)","type":"conference","keyword":["Neural network","Concept learning","Description logics"],"department":[{"_id":"574"},{"_id":"760"}],"date_created":"2022-10-15T19:20:11Z","date_updated":"2023-07-02T18:10:02Z","publication_status":"published","intvolume":"     13870","year":"2023","title":"Neural Class Expression Synthesis","author":[{"id":"87189","full_name":"KOUAGOU, N'Dah Jean","last_name":"KOUAGOU","first_name":"N'Dah Jean"},{"full_name":"Heindorf, Stefan","first_name":"Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871"},{"last_name":"Demir","first_name":"Caglar","full_name":"Demir, Caglar","id":"43817"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"}],"publication_identifier":{"unknown":["978-3-031-33455-9"]},"doi":"https://doi.org/10.1007/978-3-031-33455-9_13","main_file_link":[{"url":"https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"project":[{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"},{"name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs","_id":"407","grant_number":"101070305"},{"name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems","grant_number":"NW21-059D","_id":"285"}],"citation":{"mla":"KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” <i>The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>, edited by Catia Pesquita et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:<a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>.","ama":"KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis. In: Pesquita C, Jimenez-Ruiz E, McCusker J, et al., eds. <i>The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>. Vol 13870. Springer International Publishing; 2023:209-226. doi:<a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>","bibtex":"@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis}, volume={13870}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>}, booktitle={The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}, publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, editor={Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}, year={2023}, pages={209–226} }","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, &#38; S. Hertling (Eds.), <i>The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)</i> (Vol. 13870, pp. 209–226). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>","ieee":"N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis,” in <i>The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>, Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi: <a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>.","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis.” In <i>The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)</i>, edited by Catia Pesquita, Ernesto Jimenez-Ruiz, Jamie McCusker, Daniel Faria, Mauro Dragoni, Anastasia Dimou, Raphael Troncy, and Sven Hertling, 13870:209–26. Springer International Publishing, 2023. <a href=\"https://doi.org/10.1007/978-3-031-33455-9_13\">https://doi.org/10.1007/978-3-031-33455-9_13</a>.","short":"N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Springer International Publishing, 2023, pp. 209–226."},"oa":"1","external_id":{"unknown":["https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13"]},"status":"public","conference":{"location":"Hersonissos, Crete, Greece","start_date":"2023-05-28","name":"20th Extended Semantic Web Conference","end_date":"2023-06-01"},"user_id":"11871","editor":[{"full_name":"Pesquita, Catia","first_name":"Catia","last_name":"Pesquita"},{"full_name":"Jimenez-Ruiz, Ernesto","last_name":"Jimenez-Ruiz","first_name":"Ernesto"},{"full_name":"McCusker, Jamie","first_name":"Jamie","last_name":"McCusker"},{"first_name":"Daniel","last_name":"Faria","full_name":"Faria, Daniel"},{"last_name":"Dragoni","first_name":"Mauro","full_name":"Dragoni, Mauro"},{"full_name":"Dimou, Anastasia","last_name":"Dimou","first_name":"Anastasia"},{"last_name":"Troncy","first_name":"Raphael","full_name":"Troncy, Raphael"},{"full_name":"Hertling, Sven","first_name":"Sven","last_name":"Hertling"}],"volume":13870,"page":"209 - 226","publisher":"Springer International Publishing","_id":"33734"},{"status":"public","title":"Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras","year":"2023","conference":{"location":"Torino","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases"},"author":[{"id":"43817","full_name":"Demir, Caglar","first_name":"Caglar","last_name":"Demir"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"date_updated":"2023-08-01T09:22:40Z","has_accepted_license":"1","language":[{"iso":"eng"}],"_id":"46243","ddc":["000"],"user_id":"43817","publication":"ECML-PKDD","file_date_updated":"2023-08-01T09:11:59Z","citation":{"mla":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras.” <i>ECML-PKDD</i>, 2023.","bibtex":"@article{Demir_Ngonga Ngomo_2023, title={Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras}, journal={ECML-PKDD}, author={Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","ama":"Demir C, Ngonga Ngomo A-C. Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras. <i>ECML-PKDD</i>. Published online 2023.","ieee":"C. Demir and A.-C. Ngonga Ngomo, “Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras,” <i>ECML-PKDD</i>, 2023.","apa":"Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras. <i>ECML-PKDD</i>. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Torino.","short":"C. Demir, A.-C. Ngonga Ngomo, ECML-PKDD (2023).","chicago":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras.” <i>ECML-PKDD</i>, 2023."},"project":[{"grant_number":"101070305","_id":"407","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs"},{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"},{"name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems","grant_number":"NW21-059D","_id":"285"}],"file":[{"date_created":"2023-08-01T09:11:59Z","creator":"cdemir","content_type":"application/pdf","file_id":"46244","file_size":408352,"access_level":"open_access","file_name":"public.pdf","date_updated":"2023-08-01T09:11:59Z","relation":"main_file"}],"date_created":"2023-08-01T09:12:06Z","type":"journal_article","oa":"1"},{"status":"public","title":"Neuro-Symbolic Class Expression Learning","year":"2023","author":[{"id":"43817","first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille"}],"conference":{"name":"International Joint Conference on Artificial Intelligence IJCAI 2023","location":"Macau"},"date_updated":"2023-08-01T09:44:30Z","has_accepted_license":"1","_id":"46251","language":[{"iso":"eng"}],"user_id":"43817","ddc":["000"],"file_date_updated":"2023-08-01T09:30:35Z","publication":"International Joint Conference on Artificial Intelligence","citation":{"ama":"Demir C, Ngonga Ngomo A-C. Neuro-Symbolic Class Expression Learning. <i>International Joint Conference on Artificial Intelligence</i>. Published online 2023.","bibtex":"@article{Demir_Ngonga Ngomo_2023, title={Neuro-Symbolic Class Expression Learning}, journal={International Joint Conference on Artificial Intelligence}, author={Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","mla":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Neuro-Symbolic Class Expression Learning.” <i>International Joint Conference on Artificial Intelligence</i>, 2023.","short":"C. Demir, A.-C. Ngonga Ngomo, International Joint Conference on Artificial Intelligence (2023).","chicago":"Demir, Caglar, and Axel-Cyrille Ngonga Ngomo. “Neuro-Symbolic Class Expression Learning.” <i>International Joint Conference on Artificial Intelligence</i>, 2023.","apa":"Demir, C., &#38; Ngonga Ngomo, A.-C. (2023). Neuro-Symbolic Class Expression Learning. <i>International Joint Conference on Artificial Intelligence</i>. International Joint Conference on Artificial Intelligence IJCAI 2023, Macau.","ieee":"C. Demir and A.-C. Ngonga Ngomo, “Neuro-Symbolic Class Expression Learning,” <i>International Joint Conference on Artificial Intelligence</i>, 2023."},"project":[{"grant_number":"101070305","_id":"407","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs"},{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"},{"_id":"285","grant_number":"NW21-059D","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems"}],"file":[{"date_created":"2023-08-01T09:30:35Z","creator":"cdemir","file_id":"46252","content_type":"application/pdf","relation":"main_file","date_updated":"2023-08-01T09:30:35Z","file_name":"public.pdf","file_size":340865,"access_level":"open_access"}],"date_created":"2023-08-01T09:30:37Z","type":"journal_article","department":[{"_id":"574"}],"oa":"1"},{"date_created":"2022-05-31T07:04:36Z","type":"preprint","oa":"1","publication":"arXiv:2205.06560","citation":{"bibtex":"@article{Demir_Lienen_Ngonga Ngomo_2022, title={Kronecker Decomposition for Knowledge Graph Embeddings}, journal={arXiv:2205.06560}, author={Demir, Caglar and Lienen, Julian and Ngonga Ngomo, Axel-Cyrille}, year={2022} }","ama":"Demir C, Lienen J, Ngonga Ngomo A-C. Kronecker Decomposition for Knowledge Graph Embeddings. <i>arXiv:220506560</i>. Published online 2022.","mla":"Demir, Caglar, et al. “Kronecker Decomposition for Knowledge Graph Embeddings.” <i>ArXiv:2205.06560</i>, 2022.","chicago":"Demir, Caglar, Julian Lienen, and Axel-Cyrille Ngonga Ngomo. “Kronecker Decomposition for Knowledge Graph Embeddings.” <i>ArXiv:2205.06560</i>, 2022.","short":"C. Demir, J. Lienen, A.-C. Ngonga Ngomo, ArXiv:2205.06560 (2022).","ieee":"C. Demir, J. Lienen, and A.-C. Ngonga Ngomo, “Kronecker Decomposition for Knowledge Graph Embeddings,” <i>arXiv:2205.06560</i>. 2022.","apa":"Demir, C., Lienen, J., &#38; Ngonga Ngomo, A.-C. (2022). Kronecker Decomposition for Knowledge Graph Embeddings. In <i>arXiv:2205.06560</i>."},"abstract":[{"text":"Knowledge graph embedding research has mainly focused on learning continuous representations of entities and relations tailored towards the link prediction problem. Recent results indicate an ever increasing predictive ability of current approaches on benchmark datasets. However, this effectiveness often comes with the cost of over-parameterization and increased computationally complexity. The former induces extensive hyperparameter optimization to mitigate malicious overfitting. The latter magnifies the importance of winning the hardware lottery. Here, we investigate a remedy for the first problem. We propose a technique based on Kronecker decomposition to reduce the number of parameters in a knowledge graph embedding model, while retaining its expressiveness. Through Kronecker decomposition, large embedding matrices are split into smaller embedding matrices during the training process. Hence, embeddings of knowledge graphs are not plainly retrieved but reconstructed on the fly. The decomposition ensures that elementwise interactions between three embedding vectors are extended with interactions within each embedding vector. This implicitly reduces redundancy in embedding vectors and encourages feature reuse. To quantify the impact of applying Kronecker decomposition on embedding matrices, we conduct a series of experiments on benchmark datasets. Our experiments suggest that applying Kronecker decomposition on embedding matrices leads to an improved parameter efficiency on all benchmark datasets. Moreover, empirical evidence suggests that reconstructed embeddings entail robustness against noise in the input knowledge graph. To foster reproducible research, we provide an open-source implementation of our approach, including training and evaluation scripts as well as pre-trained models in our knowledge graph embedding framework.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2205.06560"}],"language":[{"iso":"eng"}],"_id":"31545","user_id":"44040","title":"Kronecker Decomposition for Knowledge Graph Embeddings","year":"2022","status":"public","author":[{"full_name":"Demir, Caglar","last_name":"Demir","first_name":"Caglar","id":"43817"},{"id":"44040","full_name":"Lienen, Julian","last_name":"Lienen","first_name":"Julian"},{"id":"65716","first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"date_updated":"2022-05-31T07:05:50Z"},{"user_id":"44040","_id":"31546","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://arxiv.org/abs/2205.15239","open_access":"1"}],"date_updated":"2022-05-31T07:05:54Z","author":[{"id":"44040","first_name":"Julian","last_name":"Lienen","full_name":"Lienen, Julian"},{"first_name":"Caglar","last_name":"Demir","full_name":"Demir, Caglar","id":"43817"},{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129"}],"status":"public","year":"2022","title":"Conformal Credal Self-Supervised Learning","oa":"1","type":"preprint","date_created":"2022-05-31T07:05:36Z","abstract":[{"text":"In semi-supervised learning, the paradigm of self-training refers to the idea of learning from pseudo-labels suggested by the learner itself. Across various domains, corresponding methods have proven effective and achieve state-of-the-art performance. However, pseudo-labels typically stem from ad-hoc heuristics, relying on the quality of the predictions though without guaranteeing their validity. One such method, so-called credal self-supervised learning, maintains pseudo-supervision in the form of sets of (instead of single) probability distributions over labels, thereby allowing for a flexible yet uncertainty-aware labeling. Again, however, there is no justification beyond empirical effectiveness. To address this deficiency, we make use of conformal prediction, an approach that comes with guarantees on the validity of set-valued predictions. As a result, the construction of credal sets of labels is supported by a rigorous theoretical foundation, leading to better calibrated and less error-prone supervision for unlabeled data. Along with this, we present effective algorithms for learning from credal self-supervision. An empirical study demonstrates excellent calibration properties of the pseudo-supervision, as well as the competitiveness of our method on several benchmark datasets.","lang":"eng"}],"citation":{"ieee":"J. Lienen, C. Demir, and E. Hüllermeier, “Conformal Credal Self-Supervised Learning,” <i>arXiv:2205.15239</i>. 2022.","apa":"Lienen, J., Demir, C., &#38; Hüllermeier, E. (2022). Conformal Credal Self-Supervised Learning. In <i>arXiv:2205.15239</i>.","short":"J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).","chicago":"Lienen, Julian, Caglar Demir, and Eyke Hüllermeier. “Conformal Credal Self-Supervised Learning.” <i>ArXiv:2205.15239</i>, 2022.","mla":"Lienen, Julian, et al. “Conformal Credal Self-Supervised Learning.” <i>ArXiv:2205.15239</i>, 2022.","bibtex":"@article{Lienen_Demir_Hüllermeier_2022, title={Conformal Credal Self-Supervised Learning}, journal={arXiv:2205.15239}, author={Lienen, Julian and Demir, Caglar and Hüllermeier, Eyke}, year={2022} }","ama":"Lienen J, Demir C, Hüllermeier E. Conformal Credal Self-Supervised Learning. <i>arXiv:220515239</i>. Published online 2022."},"publication":"arXiv:2205.15239"}]