[{"user_id":"11871","abstract":[{"lang":"eng","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"}],"date_created":"2022-10-15T19:20:11Z","status":"public","volume":13870,"keyword":["Neural network","Concept learning","Description logics"],"publication":"The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)","author":[{"full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean","id":"87189","last_name":"KOUAGOU"},{"full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"full_name":"Demir, Caglar","first_name":"Caglar","id":"43817","last_name":"Demir"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"publisher":"Springer International Publishing","conference":{"location":"Hersonissos, Crete, Greece","name":"20th Extended Semantic Web Conference","start_date":"2023-05-28","end_date":"2023-06-01"},"intvolume":" 13870","_id":"33734","page":"209 - 226","type":"conference","year":"2023","citation":{"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.","ieee":"N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis,” in The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi: https://doi.org/10.1007/978-3-031-33455-9_13.","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. The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023). Vol 13870. Springer International Publishing; 2023:209-226. doi:https://doi.org/10.1007/978-3-031-33455-9_13","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., & 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, & S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226). Springer International Publishing. https://doi.org/10.1007/978-3-031-33455-9_13","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis.” In The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), 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. https://doi.org/10.1007/978-3-031-33455-9_13.","bibtex":"@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis}, volume={13870}, DOI={https://doi.org/10.1007/978-3-031-33455-9_13}, 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} }","mla":"KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:https://doi.org/10.1007/978-3-031-33455-9_13."},"main_file_link":[{"open_access":"1","url":"https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf"}],"title":"Neural Class Expression Synthesis","external_id":{"unknown":["https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13"]},"project":[{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"},{"_id":"407","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs","grant_number":"101070305"},{"_id":"285","grant_number":"NW21-059D","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems"}],"publication_identifier":{"unknown":["978-3-031-33455-9"]},"publication_status":"published","editor":[{"last_name":"Pesquita","full_name":"Pesquita, Catia","first_name":"Catia"},{"last_name":"Jimenez-Ruiz","full_name":"Jimenez-Ruiz, Ernesto","first_name":"Ernesto"},{"full_name":"McCusker, Jamie","first_name":"Jamie","last_name":"McCusker"},{"last_name":"Faria","full_name":"Faria, Daniel","first_name":"Daniel"},{"last_name":"Dragoni","full_name":"Dragoni, Mauro","first_name":"Mauro"},{"first_name":"Anastasia","full_name":"Dimou, Anastasia","last_name":"Dimou"},{"first_name":"Raphael","full_name":"Troncy, Raphael","last_name":"Troncy"},{"first_name":"Sven","full_name":"Hertling, Sven","last_name":"Hertling"}],"department":[{"_id":"574"},{"_id":"760"}],"oa":"1","doi":"https://doi.org/10.1007/978-3-031-33455-9_13","date_updated":"2023-07-02T18:10:02Z","language":[{"iso":"eng"}]},{"language":[{"iso":"eng"}],"year":"2023","citation":{"short":"L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023).","ieee":"L. N. Sieger, S. Heindorf, L. Blübaum, and A.-C. Ngonga Ngomo, “Counterfactual Explanations for Concepts in ELH,” arXiv:2301.05109. 2023.","chicago":"Sieger, Leonie Nora, Stefan Heindorf, Lukas Blübaum, and Axel-Cyrille Ngonga Ngomo. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023.","apa":"Sieger, L. N., Heindorf, S., Blübaum, L., & Ngonga Ngomo, A.-C. (2023). Counterfactual Explanations for Concepts in ELH. In arXiv:2301.05109.","ama":"Sieger LN, Heindorf S, Blübaum L, Ngonga Ngomo A-C. Counterfactual Explanations for Concepts in ELH. arXiv:230105109. Published online 2023.","mla":"Sieger, Leonie Nora, et al. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023.","bibtex":"@article{Sieger_Heindorf_Blübaum_Ngonga Ngomo_2023, title={Counterfactual Explanations for Concepts in ELH}, journal={arXiv:2301.05109}, author={Sieger, Leonie Nora and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille}, year={2023} }"},"type":"preprint","main_file_link":[{"url":"https://arxiv.org/pdf/2301.05109.pdf"}],"date_updated":"2023-07-02T18:10:34Z","_id":"37937","date_created":"2023-01-22T19:36:01Z","status":"public","publication":"arXiv:2301.05109","department":[{"_id":"574"},{"_id":"760"}],"author":[{"id":"93402","last_name":"Sieger","full_name":"Sieger, Leonie Nora","first_name":"Leonie Nora"},{"id":"11871","last_name":"Heindorf","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","first_name":"Stefan"},{"first_name":"Lukas","full_name":"Blübaum, Lukas","last_name":"Blübaum"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"user_id":"11871","title":"Counterfactual Explanations for Concepts in ELH","abstract":[{"lang":"eng","text":"Knowledge bases are widely used for information management on the web,\r\nenabling high-impact applications such as web search, question answering, and\r\nnatural language processing. They also serve as the backbone for automatic\r\ndecision systems, e.g. for medical diagnostics and credit scoring. As\r\nstakeholders affected by these decisions would like to understand their\r\nsituation and verify fair decisions, a number of explanation approaches have\r\nbeen proposed using concepts in description logics. However, the learned\r\nconcepts can become long and difficult to fathom for non-experts, even when\r\nverbalized. Moreover, long concepts do not immediately provide a clear path of\r\naction to change one's situation. Counterfactuals answering the question \"How\r\nmust feature values be changed to obtain a different classification?\" have been\r\nproposed as short, human-friendly explanations for tabular data. In this paper,\r\nwe transfer the notion of counterfactuals to description logics and propose the\r\nfirst algorithm for generating counterfactual explanations in the description\r\nlogic $\\mathcal{ELH}$. Counterfactual candidates are generated from concepts\r\nand the candidates with fewest feature changes are selected as counterfactuals.\r\nIn case of multiple counterfactuals, we rank them according to the likeliness\r\nof their feature combinations. For evaluation, we conduct a user survey to\r\ninvestigate which of the generated counterfactual candidates are preferred for\r\nexplanation by participants. In a second study, we explore possible use cases\r\nfor counterfactual explanations."}],"external_id":{"arxiv":["2301.05109"]}},{"title":"Accelerating Concept Learning via Sampling","ddc":["000"],"user_id":"11871","department":[{"_id":"760"}],"file_date_updated":"2023-08-19T08:08:39Z","publication":"CIKM","author":[{"last_name":"Baci","first_name":"Alkid","full_name":"Baci, Alkid"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan"}],"file":[{"relation":"main_file","content_type":"application/pdf","date_updated":"2023-08-19T08:08:39Z","creator":"heindorf","file_id":"46577","file_size":523067,"access_level":"open_access","file_name":"baci2023_CIKM.pdf","date_created":"2023-08-19T08:08:39Z"}],"date_created":"2023-08-19T08:02:54Z","status":"public","has_accepted_license":"1","_id":"46575","date_updated":"2023-08-19T08:08:53Z","oa":"1","year":"2023","citation":{"short":"A. Baci, S. Heindorf, in: CIKM, 2023.","ieee":"A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” 2023.","chicago":"Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.” In CIKM, 2023.","apa":"Baci, A., & Heindorf, S. (2023). Accelerating Concept Learning via Sampling. CIKM.","ama":"Baci A, Heindorf S. Accelerating Concept Learning via Sampling. In: CIKM. ; 2023.","mla":"Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.” CIKM, 2023.","bibtex":"@inproceedings{Baci_Heindorf_2023, title={Accelerating Concept Learning via Sampling}, booktitle={CIKM}, author={Baci, Alkid and Heindorf, Stefan}, year={2023} }"},"type":"conference","language":[{"iso":"eng"}]},{"status":"public","date_created":"2023-09-25T13:42:01Z","publication_identifier":{"isbn":["9783031434204","9783031434211"],"issn":["0302-9743","1611-3349"]},"publication_status":"published","publisher":"Springer Nature Switzerland","author":[{"id":"87189","last_name":"Kouagou","full_name":"Kouagou, N'Dah Jean","first_name":"N'Dah Jean"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"id":"43817","last_name":"Demir","full_name":"Demir, Caglar","first_name":"Caglar"},{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"}],"department":[{"_id":"760"},{"_id":"574"}],"publication":"Machine Learning and Knowledge Discovery in Databases: Research Track","user_id":"11871","title":"Neural Class Expression Synthesis in ALCHIQ(D)","place":"Cham","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"}],"language":[{"iso":"eng"}],"year":"2023","type":"book_chapter","citation":{"ieee":"N. J. Kouagou, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis in ALCHIQ(D),” in Machine Learning and Knowledge Discovery in Databases: Research Track, Cham: Springer Nature Switzerland, 2023.","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.","mla":"Kouagou, N’Dah Jean, et al. “Neural Class Expression Synthesis in ALCHIQ(D).” Machine Learning and Knowledge Discovery in Databases: Research Track, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-43421-1_12.","bibtex":"@inbook{Kouagou_Heindorf_Demir_Ngonga Ngomo_2023, place={Cham}, title={Neural Class Expression Synthesis in ALCHIQ(D)}, DOI={10.1007/978-3-031-43421-1_12}, 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: Machine Learning and Knowledge Discovery in Databases: Research Track. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-43421-1_12","apa":"Kouagou, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis in ALCHIQ(D). In Machine Learning and Knowledge Discovery in Databases: Research Track. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Turin. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43421-1_12","chicago":"Kouagou, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis in ALCHIQ(D).” In Machine Learning and Knowledge Discovery in Databases: Research Track. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-43421-1_12."},"doi":"10.1007/978-3-031-43421-1_12","date_updated":"2023-11-21T09:20:31Z","_id":"47421","conference":{"location":"Turin","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases","start_date":"2023-09-18","end_date":"2023-09-22"}},{"title":"Class Expression Learning with Multiple Representations","user_id":"14931","author":[{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"},{"id":"43817","last_name":"Demir","full_name":"Demir, Caglar","first_name":"Caglar"},{"last_name":"Kouagou","id":"87189","first_name":"N'Dah Jean","full_name":"Kouagou, N'Dah Jean"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"full_name":"Karalis, Nikoloas","first_name":"Nikoloas","last_name":"Karalis"},{"first_name":"Alexander","full_name":"Bigerl, Alexander","last_name":"Bigerl","id":"72857"}],"publisher":"IOS Press","publication":"Compendium of Neurosymbolic Artificial Intelligence","department":[{"_id":"760"},{"_id":"574"}],"status":"public","date_created":"2023-08-08T11:49:51Z","_id":"46460","date_updated":"2023-11-21T08:06:20Z","citation":{"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.","ieee":"A.-C. Ngonga Ngomo, C. Demir, N. J. Kouagou, S. Heindorf, N. Karalis, and A. Bigerl, “Class Expression Learning with Multiple Representations,” in Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 272–286.","apa":"Ngonga Ngomo, A.-C., Demir, C., Kouagou, N. J., Heindorf, S., Karalis, N., & Bigerl, A. (2023). Class Expression Learning with Multiple Representations. In Compendium of Neurosymbolic Artificial Intelligence (pp. 272–286). IOS Press.","ama":"Ngonga Ngomo A-C, Demir C, Kouagou NJ, Heindorf S, Karalis N, Bigerl A. Class Expression Learning with Multiple Representations. In: Compendium of Neurosymbolic Artificial Intelligence. IOS Press; 2023:272–286.","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 Compendium of Neurosymbolic Artificial Intelligence, 272–286. IOS Press, 2023.","mla":"Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple Representations.” Compendium of Neurosymbolic Artificial Intelligence, IOS Press, 2023, pp. 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} }"},"type":"book_chapter","year":"2023","page":"272–286","language":[{"iso":"eng"}]},{"language":[{"iso":"eng"}],"citation":{"apa":"Demir, C., Wiebesiek, M., Lu, R., Ngonga Ngomo, A.-C., & Heindorf, S. (2023). LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals. ECML PKDD. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Torino.","ama":"Demir C, Wiebesiek M, Lu R, Ngonga Ngomo A-C, Heindorf S. LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals. ECML PKDD. Published online 2023.","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.” ECML PKDD, 2023.","mla":"Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals.” ECML PKDD, 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} }","short":"C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (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,” ECML PKDD, 2023."},"type":"journal_article","year":"2023","oa":"1","_id":"46248","date_updated":"2024-03-06T16:18:53Z","conference":{"location":"Torino","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases"},"status":"public","has_accepted_license":"1","date_created":"2023-08-01T09:24:21Z","project":[{"_id":"407","grant_number":"101070305","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs"},{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","grant_number":"860801","_id":"410"},{"_id":"285","grant_number":"NW21-059D","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems"}],"file":[{"relation":"main_file","date_updated":"2023-08-01T09:24:15Z","content_type":"application/pdf","file_id":"46249","creator":"cdemir","file_size":562759,"access_level":"open_access","date_created":"2023-08-01T09:24:15Z","file_name":"public.pdf"}],"author":[{"first_name":"Caglar","full_name":"Demir, Caglar","last_name":"Demir","id":"43817"},{"full_name":"Wiebesiek, Michel","first_name":"Michel","last_name":"Wiebesiek"},{"first_name":"Renzhong","full_name":"Lu, Renzhong","last_name":"Lu"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"}],"file_date_updated":"2023-08-01T09:24:15Z","publication":"ECML PKDD","department":[{"_id":"574"},{"_id":"760"}],"user_id":"14931","title":"LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals","ddc":["000"]},{"_id":"33740","main_file_link":[{"url":"https://arxiv.org/abs/2107.04911","open_access":"1"}],"type":"book_chapter","year":"2022","citation":{"ama":"KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Learning Concept Lengths Accelerates Concept Learning in ALC. In: The Semantic Web. Springer International Publishing; 2022. doi:10.1007/978-3-031-06981-9_14","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2022). Learning Concept Lengths Accelerates Concept Learning in ALC. In The Semantic Web. Springer International Publishing. https://doi.org/10.1007/978-3-031-06981-9_14","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Learning Concept Lengths Accelerates Concept Learning in ALC.” In The Semantic Web. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-06981-9_14.","bibtex":"@inbook{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2022, place={Cham}, title={Learning Concept Lengths Accelerates Concept Learning in ALC}, DOI={10.1007/978-3-031-06981-9_14}, booktitle={The Semantic Web}, publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2022} }","mla":"KOUAGOU, N’Dah Jean, et al. “Learning Concept Lengths Accelerates Concept Learning in ALC.” The Semantic Web, Springer International Publishing, 2022, doi:10.1007/978-3-031-06981-9_14.","short":"N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: The Semantic Web, Springer International Publishing, Cham, 2022.","ieee":"N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Learning Concept Lengths Accelerates Concept Learning in ALC,” in The Semantic Web, Cham: Springer International Publishing, 2022."},"user_id":"11871","author":[{"last_name":"KOUAGOU","id":"87189","first_name":"N'Dah Jean","full_name":"KOUAGOU, N'Dah Jean"},{"id":"11871","last_name":"Heindorf","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","first_name":"Stefan"},{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"publisher":"Springer International Publishing","publication":"The Semantic Web","status":"public","date_created":"2022-10-15T19:34:41Z","date_updated":"2022-10-15T19:52:08Z","doi":"10.1007/978-3-031-06981-9_14","oa":"1","language":[{"iso":"eng"}],"place":"Cham","title":"Learning Concept Lengths Accelerates Concept Learning in ALC","related_material":{"link":[{"relation":"confirmation","url":"https://link.springer.com/chapter/10.1007/978-3-031-06981-9_14"}]},"department":[{"_id":"574"}],"publication_identifier":{"isbn":["9783031069802","9783031069819"],"issn":["0302-9743","1611-3349"]},"publication_status":"published"},{"oa":"1","date_updated":"2022-10-16T08:49:22Z","_id":"29290","language":[{"iso":"eng"}],"page":"818-828","type":"conference","citation":{"ieee":"S. Heindorf et al., “EvoLearner: Learning Description Logics with Evolutionary Algorithms,” in WWW, 2022, pp. 818–828.","short":"S. Heindorf, L. Blübaum, N. Düsterhus, T. Werner, V.N. Golani, C. Demir, A.-C. Ngonga Ngomo, in: WWW, ACM, 2022, pp. 818–828.","bibtex":"@inproceedings{Heindorf_Blübaum_Düsterhus_Werner_Golani_Demir_Ngonga Ngomo_2022, title={EvoLearner: Learning Description Logics with Evolutionary Algorithms}, booktitle={WWW}, publisher={ACM}, author={Heindorf, Stefan and Blübaum, Lukas and Düsterhus, Nick and Werner, Till and Golani, Varun Nandkumar and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, year={2022}, pages={818–828} }","mla":"Heindorf, Stefan, et al. “EvoLearner: Learning Description Logics with Evolutionary Algorithms.” WWW, ACM, 2022, pp. 818–28.","ama":"Heindorf S, Blübaum L, Düsterhus N, et al. EvoLearner: Learning Description Logics with Evolutionary Algorithms. In: WWW. ACM; 2022:818-828.","apa":"Heindorf, S., Blübaum, L., Düsterhus, N., Werner, T., Golani, V. N., Demir, C., & Ngonga Ngomo, A.-C. (2022). EvoLearner: Learning Description Logics with Evolutionary Algorithms. WWW, 818–828.","chicago":"Heindorf, Stefan, Lukas Blübaum, Nick Düsterhus, Till Werner, Varun Nandkumar Golani, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “EvoLearner: Learning Description Logics with Evolutionary Algorithms.” In WWW, 818–28. ACM, 2022."},"year":"2022","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2111.04879"}],"user_id":"11871","title":"EvoLearner: Learning Description Logics with Evolutionary Algorithms","abstract":[{"lang":"eng","text":"Classifying nodes in knowledge graphs is an important task, e.g., predicting\r\nmissing types of entities, predicting which molecules cause cancer, or\r\npredicting which drugs are promising treatment candidates. While black-box\r\nmodels often achieve high predictive performance, they are only post-hoc and\r\nlocally explainable and do not allow the learned model to be easily enriched\r\nwith domain knowledge. Towards this end, learning description logic concepts\r\nfrom positive and negative examples has been proposed. However, learning such\r\nconcepts often takes a long time and state-of-the-art approaches provide\r\nlimited support for literal data values, although they are crucial for many\r\napplications. In this paper, we propose EvoLearner - an evolutionary approach\r\nto learn ALCQ(D), which is the attributive language with complement (ALC)\r\npaired with qualified cardinality restrictions (Q) and data properties (D). We\r\ncontribute a novel initialization method for the initial population: starting\r\nfrom positive examples (nodes in the knowledge graph), we perform biased random\r\nwalks and translate them to description logic concepts. Moreover, we improve\r\nsupport for data properties by maximizing information gain when deciding where\r\nto split the data. We show that our approach significantly outperforms the\r\nstate of the art on the benchmarking framework SML-Bench for structured machine\r\nlearning. Our ablation study confirms that this is due to our novel\r\ninitialization method and support for data properties."}],"date_created":"2022-01-12T10:22:53Z","status":"public","publication":"WWW","department":[{"_id":"574"}],"publisher":"ACM","author":[{"first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","last_name":"Heindorf","id":"11871"},{"last_name":"Blübaum","first_name":"Lukas","full_name":"Blübaum, Lukas"},{"first_name":"Nick","full_name":"Düsterhus, Nick","last_name":"Düsterhus"},{"last_name":"Werner","full_name":"Werner, Till","first_name":"Till"},{"first_name":"Varun Nandkumar","full_name":"Golani, Varun Nandkumar","last_name":"Golani"},{"full_name":"Demir, Caglar","first_name":"Caglar","id":"43817","last_name":"Demir"},{"last_name":"Ngonga Ngomo","id":"65716","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}]},{"citation":{"short":"L.N. Sieger, J. Hermann, A. Schomäcker, S. Heindorf, C. Meske, C.-C. Hey, A. Doğangün, in: International Conference on Human-Agent Interaction, ACM, 2022.","ieee":"L. N. Sieger et al., “User Involvement in Training Smart Home Agents,” presented at the HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand, 2022, doi: 10.1145/3527188.3561914.","chicago":"Sieger, Leonie Nora, Julia Hermann, Astrid Schomäcker, Stefan Heindorf, Christian Meske, Celine-Chiara Hey, and Ayşegül Doğangün. “User Involvement in Training Smart Home Agents.” In International Conference on Human-Agent Interaction. ACM, 2022. https://doi.org/10.1145/3527188.3561914.","ama":"Sieger LN, Hermann J, Schomäcker A, et al. User Involvement in Training Smart Home Agents. In: International Conference on Human-Agent Interaction. ACM; 2022. doi:10.1145/3527188.3561914","apa":"Sieger, L. N., Hermann, J., Schomäcker, A., Heindorf, S., Meske, C., Hey, C.-C., & Doğangün, A. (2022). User Involvement in Training Smart Home Agents. International Conference on Human-Agent Interaction. HAI ’22: International Conference on Human-Agent Interaction, Christchurch, New Zealand. https://doi.org/10.1145/3527188.3561914","mla":"Sieger, Leonie Nora, et al. “User Involvement in Training Smart Home Agents.” International Conference on Human-Agent Interaction, ACM, 2022, doi:10.1145/3527188.3561914.","bibtex":"@inproceedings{Sieger_Hermann_Schomäcker_Heindorf_Meske_Hey_Doğangün_2022, title={User Involvement in Training Smart Home Agents}, DOI={10.1145/3527188.3561914}, booktitle={International Conference on Human-Agent Interaction}, publisher={ACM}, author={Sieger, Leonie Nora and Hermann, Julia and Schomäcker, Astrid and Heindorf, Stefan and Meske, Christian and Hey, Celine-Chiara and Doğangün, Ayşegül}, year={2022} }"},"type":"conference","year":"2022","main_file_link":[{"url":"https://papers.dice-research.org/2022/HAI_SmartHome/User_Involvement_in_Training_Smart_Home_Agents_public.pdf"}],"_id":"34674","conference":{"location":"Christchurch, New Zealand","name":"HAI '22: International Conference on Human-Agent Interaction","start_date":"2022-12-05","end_date":"2022-12-08"},"alternative_title":["Increasing Perceived Control and Understanding"],"status":"public","date_created":"2022-12-21T09:48:43Z","author":[{"first_name":"Leonie Nora","full_name":"Sieger, Leonie Nora","last_name":"Sieger","id":"93402"},{"last_name":"Hermann","first_name":"Julia","full_name":"Hermann, Julia"},{"last_name":"Schomäcker","first_name":"Astrid","full_name":"Schomäcker, Astrid"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"last_name":"Meske","first_name":"Christian","full_name":"Meske, Christian"},{"last_name":"Hey","first_name":"Celine-Chiara","full_name":"Hey, Celine-Chiara"},{"last_name":"Doğangün","full_name":"Doğangün, Ayşegül","first_name":"Ayşegül"}],"quality_controlled":"1","publisher":"ACM","publication":"International Conference on Human-Agent Interaction","keyword":["human-agent interaction","smart homes","supervised learning","participation"],"user_id":"14931","abstract":[{"lang":"eng","text":"Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation."}],"language":[{"iso":"eng"}],"doi":"10.1145/3527188.3561914","date_updated":"2023-02-09T14:48:51Z","publication_status":"published","project":[{"name":"TRR 318 - B1: TRR 318 - Subproject B1","_id":"121"}],"department":[{"_id":"574"},{"_id":"760"}],"title":"User Involvement in Training Smart Home Agents"},{"place":"Cham","title":"Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings","user_id":"72768","department":[{"_id":"574"}],"publication":"The Semantic Web: ESWC 2022 Satellite Events","publisher":"Springer International Publishing","author":[{"first_name":"Hamada Mohamed Abdelsamee","orcid":"0000-0003-0215-1278","full_name":"Zahera, Hamada Mohamed Abdelsamee","last_name":"Zahera","id":"72768"},{"first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","last_name":"Heindorf","id":"11871"},{"last_name":"Balke","first_name":"Stefan","full_name":"Balke, Stefan"},{"last_name":"Haupt","full_name":"Haupt, Jonas","first_name":"Jonas"},{"full_name":"Voigt, Martin","first_name":"Martin","last_name":"Voigt"},{"first_name":"Carolin","full_name":"Walter, Carolin","last_name":"Walter"},{"full_name":"Witter, Fabian","first_name":"Fabian","last_name":"Witter"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"publication_status":"published","publication_identifier":{"isbn":["9783031116087","9783031116094"],"issn":["0302-9743","1611-3349"]},"date_created":"2022-10-15T19:25:42Z","status":"public","_id":"33738","date_updated":"2023-06-23T09:20:20Z","doi":"10.1007/978-3-031-11609-4_9","oa":"1","main_file_link":[{"open_access":"1","url":"https://2022.eswc-conferences.org/wp-content/uploads/2022/05/pd_Zahera_et_al_paper_230.pdf"}],"type":"book_chapter","citation":{"short":"H.M.A. Zahera, S. Heindorf, S. Balke, J. Haupt, M. Voigt, C. Walter, F. Witter, A.-C. Ngonga Ngomo, in: The Semantic Web: ESWC 2022 Satellite Events, Springer International Publishing, Cham, 2022.","ieee":"H. M. A. Zahera et al., “Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings,” in The Semantic Web: ESWC 2022 Satellite Events, Cham: Springer International Publishing, 2022.","ama":"Zahera HMA, Heindorf S, Balke S, et al. Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings. In: The Semantic Web: ESWC 2022 Satellite Events. Springer International Publishing; 2022. doi:10.1007/978-3-031-11609-4_9","apa":"Zahera, H. M. A., Heindorf, S., Balke, S., Haupt, J., Voigt, M., Walter, C., Witter, F., & Ngonga Ngomo, A.-C. (2022). Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings. In The Semantic Web: ESWC 2022 Satellite Events. Springer International Publishing. https://doi.org/10.1007/978-3-031-11609-4_9","chicago":"Zahera, Hamada Mohamed Abdelsamee, Stefan Heindorf, Stefan Balke, Jonas Haupt, Martin Voigt, Carolin Walter, Fabian Witter, and Axel-Cyrille Ngonga Ngomo. “Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings.” In The Semantic Web: ESWC 2022 Satellite Events. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-11609-4_9.","mla":"Zahera, Hamada Mohamed Abdelsamee, et al. “Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings.” The Semantic Web: ESWC 2022 Satellite Events, Springer International Publishing, 2022, doi:10.1007/978-3-031-11609-4_9.","bibtex":"@inbook{Zahera_Heindorf_Balke_Haupt_Voigt_Walter_Witter_Ngonga Ngomo_2022, place={Cham}, title={Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings}, DOI={10.1007/978-3-031-11609-4_9}, booktitle={The Semantic Web: ESWC 2022 Satellite Events}, publisher={Springer International Publishing}, author={Zahera, Hamada Mohamed Abdelsamee and Heindorf, Stefan and Balke, Stefan and Haupt, Jonas and Voigt, Martin and Walter, Carolin and Witter, Fabian and Ngonga Ngomo, Axel-Cyrille}, year={2022} }"},"year":"2022","language":[{"iso":"eng"}]}]