[{"title":"Neural Class Expression Synthesis","external_id":{"unknown":["https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13"]},"publication_identifier":{"unknown":["978-3-031-33455-9"]},"publication_status":"published","editor":[{"full_name":"Pesquita, Catia","first_name":"Catia","last_name":"Pesquita"},{"first_name":"Ernesto","full_name":"Jimenez-Ruiz, Ernesto","last_name":"Jimenez-Ruiz"},{"first_name":"Jamie","full_name":"McCusker, Jamie","last_name":"McCusker"},{"first_name":"Daniel","full_name":"Faria, Daniel","last_name":"Faria"},{"last_name":"Dragoni","first_name":"Mauro","full_name":"Dragoni, Mauro"},{"last_name":"Dimou","full_name":"Dimou, Anastasia","first_name":"Anastasia"},{"first_name":"Raphael","full_name":"Troncy, Raphael","last_name":"Troncy"},{"first_name":"Sven","full_name":"Hertling, Sven","last_name":"Hertling"}],"project":[{"_id":"410","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale"},{"name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs","grant_number":"101070305","_id":"407"},{"_id":"285","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems","grant_number":"NW21-059D"}],"department":[{"_id":"574"},{"_id":"760"}],"doi":"https://doi.org/10.1007/978-3-031-33455-9_13","oa":"1","date_updated":"2023-07-02T18:10:02Z","language":[{"iso":"eng"}],"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"}],"volume":13870,"date_created":"2022-10-15T19:20:11Z","status":"public","keyword":["Neural network","Concept learning","Description logics"],"publication":"The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)","publisher":"Springer International Publishing","author":[{"full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean","id":"87189","last_name":"KOUAGOU"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"full_name":"Demir, Caglar","first_name":"Caglar","id":"43817","last_name":"Demir"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"conference":{"end_date":"2023-06-01","start_date":"2023-05-28","name":"20th Extended Semantic Web Conference","location":"Hersonissos, Crete, Greece"},"intvolume":" 13870","_id":"33734","page":"209 - 226","year":"2023","type":"conference","citation":{"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.","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","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","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.","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} }","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."},"main_file_link":[{"open_access":"1","url":"https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf"}]},{"date_created":"2023-01-22T19:36:01Z","status":"public","department":[{"_id":"574"},{"_id":"760"}],"publication":"arXiv:2301.05109","author":[{"full_name":"Sieger, Leonie Nora","first_name":"Leonie Nora","id":"93402","last_name":"Sieger"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"last_name":"Blübaum","first_name":"Lukas","full_name":"Blübaum, Lukas"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"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"]},"language":[{"iso":"eng"}],"year":"2023","citation":{"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} }","mla":"Sieger, Leonie Nora, et al. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023.","ama":"Sieger LN, Heindorf S, Blübaum L, Ngonga Ngomo A-C. Counterfactual Explanations for Concepts in ELH. arXiv:230105109. Published online 2023.","apa":"Sieger, L. N., Heindorf, S., Blübaum, L., & Ngonga Ngomo, A.-C. (2023). Counterfactual Explanations for Concepts in ELH. In arXiv:2301.05109.","chicago":"Sieger, Leonie Nora, Stefan Heindorf, Lukas Blübaum, and Axel-Cyrille Ngonga Ngomo. “Counterfactual Explanations for Concepts in ELH.” 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.","short":"L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023)."},"type":"preprint","main_file_link":[{"url":"https://arxiv.org/pdf/2301.05109.pdf"}],"_id":"37937","date_updated":"2023-07-02T18:10:34Z"},{"date_created":"2023-08-19T08:02:54Z","status":"public","has_accepted_license":"1","department":[{"_id":"760"}],"publication":"CIKM","file_date_updated":"2023-08-19T08:08:39Z","author":[{"last_name":"Baci","full_name":"Baci, Alkid","first_name":"Alkid"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865"}],"file":[{"date_updated":"2023-08-19T08:08:39Z","content_type":"application/pdf","relation":"main_file","file_size":523067,"creator":"heindorf","file_id":"46577","access_level":"open_access","file_name":"baci2023_CIKM.pdf","date_created":"2023-08-19T08:08:39Z"}],"ddc":["000"],"title":"Accelerating Concept Learning via Sampling","user_id":"11871","citation":{"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} }","chicago":"Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.” In CIKM, 2023.","ama":"Baci A, Heindorf S. Accelerating Concept Learning via Sampling. In: CIKM. ; 2023.","apa":"Baci, A., & Heindorf, S. (2023). Accelerating Concept Learning via Sampling. CIKM.","ieee":"A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” 2023.","short":"A. Baci, S. Heindorf, in: CIKM, 2023."},"year":"2023","type":"conference","language":[{"iso":"eng"}],"oa":"1","date_updated":"2023-08-19T08:08:53Z","_id":"46575"},{"date_created":"2023-09-25T13:42:01Z","status":"public","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031434204","9783031434211"]},"publication_status":"published","department":[{"_id":"760"},{"_id":"574"}],"publication":"Machine Learning and Knowledge Discovery in Databases: Research Track","publisher":"Springer Nature Switzerland","author":[{"last_name":"Kouagou","id":"87189","first_name":"N'Dah Jean","full_name":"Kouagou, N'Dah Jean"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"}],"user_id":"11871","title":"Neural Class Expression Synthesis in ALCHIQ(D)","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"}],"place":"Cham","language":[{"iso":"eng"}],"year":"2023","citation":{"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} }","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","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","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.","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."},"type":"book_chapter","doi":"10.1007/978-3-031-43421-1_12","conference":{"end_date":"2023-09-22","start_date":"2023-09-18","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases","location":"Turin"},"date_updated":"2023-11-21T09:20:31Z","_id":"47421"},{"user_id":"14931","title":"Class Expression Learning with Multiple Representations","date_created":"2023-08-08T11:49:51Z","status":"public","publication":"Compendium of Neurosymbolic Artificial Intelligence","department":[{"_id":"760"},{"_id":"574"}],"publisher":"IOS Press","author":[{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"},{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"first_name":"N'Dah Jean","full_name":"Kouagou, N'Dah Jean","last_name":"Kouagou","id":"87189"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"last_name":"Karalis","first_name":"Nikoloas","full_name":"Karalis, Nikoloas"},{"first_name":"Alexander","full_name":"Bigerl, Alexander","last_name":"Bigerl","id":"72857"}],"date_updated":"2023-11-21T08:06:20Z","_id":"46460","language":[{"iso":"eng"}],"page":"272–286","citation":{"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} }","mla":"Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple Representations.” Compendium of Neurosymbolic Artificial Intelligence, 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 Compendium of Neurosymbolic Artificial Intelligence, 272–286. IOS Press, 2023.","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.","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.","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.","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."},"year":"2023","type":"book_chapter"},{"oa":"1","conference":{"location":"Torino","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases"},"_id":"46248","date_updated":"2024-03-06T16:18:53Z","citation":{"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.","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.","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.","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.","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} }","mla":"Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals.” ECML PKDD, 2023."},"type":"journal_article","year":"2023","language":[{"iso":"eng"}],"ddc":["000"],"title":"LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals","user_id":"14931","date_created":"2023-08-01T09:24:21Z","project":[{"name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs","grant_number":"101070305","_id":"407"},{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","grant_number":"860801","_id":"410"},{"name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems","grant_number":"NW21-059D","_id":"285"}],"has_accepted_license":"1","status":"public","file_date_updated":"2023-08-01T09:24:15Z","publication":"ECML PKDD","department":[{"_id":"574"},{"_id":"760"}],"author":[{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"last_name":"Wiebesiek","full_name":"Wiebesiek, Michel","first_name":"Michel"},{"first_name":"Renzhong","full_name":"Lu, Renzhong","last_name":"Lu"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"},{"first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","last_name":"Heindorf","id":"11871"}],"file":[{"file_name":"public.pdf","date_created":"2023-08-01T09:24:15Z","access_level":"open_access","file_id":"46249","creator":"cdemir","file_size":562759,"relation":"main_file","content_type":"application/pdf","date_updated":"2023-08-01T09:24:15Z"}]},{"oa":"1","doi":"10.1007/978-3-031-06981-9_14","date_updated":"2022-10-15T19:52:08Z","language":[{"iso":"eng"}],"related_material":{"link":[{"relation":"confirmation","url":"https://link.springer.com/chapter/10.1007/978-3-031-06981-9_14"}]},"title":"Learning Concept Lengths Accelerates Concept Learning in ALC","place":"Cham","publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031069802","9783031069819"]},"department":[{"_id":"574"}],"_id":"33740","citation":{"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.","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.","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.","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} }"},"year":"2022","type":"book_chapter","main_file_link":[{"url":"https://arxiv.org/abs/2107.04911","open_access":"1"}],"user_id":"11871","date_created":"2022-10-15T19:34:41Z","status":"public","publication":"The Semantic Web","author":[{"id":"87189","last_name":"KOUAGOU","full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"id":"43817","last_name":"Demir","full_name":"Demir, Caglar","first_name":"Caglar"},{"last_name":"Ngonga Ngomo","id":"65716","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"publisher":"Springer International Publishing"},{"_id":"29290","date_updated":"2022-10-16T08:49:22Z","oa":"1","main_file_link":[{"url":"https://arxiv.org/abs/2111.04879","open_access":"1"}],"language":[{"iso":"eng"}],"page":"818-828","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.","mla":"Heindorf, Stefan, et al. “EvoLearner: Learning Description Logics with Evolutionary Algorithms.” WWW, ACM, 2022, pp. 818–28.","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} }","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.","ama":"Heindorf S, Blübaum L, Düsterhus N, et al. EvoLearner: Learning Description Logics with Evolutionary Algorithms. In: WWW. ACM; 2022:818-828.","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."},"type":"conference","year":"2022","abstract":[{"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.","lang":"eng"}],"user_id":"11871","title":"EvoLearner: Learning Description Logics with Evolutionary Algorithms","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"},{"full_name":"Blübaum, Lukas","first_name":"Lukas","last_name":"Blübaum"},{"last_name":"Düsterhus","full_name":"Düsterhus, Nick","first_name":"Nick"},{"first_name":"Till","full_name":"Werner, Till","last_name":"Werner"},{"first_name":"Varun Nandkumar","full_name":"Golani, Varun Nandkumar","last_name":"Golani"},{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"last_name":"Ngonga Ngomo","id":"65716","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"date_created":"2022-01-12T10:22:53Z","status":"public"},{"title":"User Involvement in Training Smart Home Agents","department":[{"_id":"574"},{"_id":"760"}],"publication_status":"published","project":[{"_id":"121","name":"TRR 318 - B1: TRR 318 - Subproject B1"}],"date_updated":"2023-02-09T14:48:51Z","doi":"10.1145/3527188.3561914","language":[{"iso":"eng"}],"abstract":[{"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.","lang":"eng"}],"user_id":"14931","author":[{"first_name":"Leonie Nora","full_name":"Sieger, Leonie Nora","last_name":"Sieger","id":"93402"},{"full_name":"Hermann, Julia","first_name":"Julia","last_name":"Hermann"},{"full_name":"Schomäcker, Astrid","first_name":"Astrid","last_name":"Schomäcker"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan"},{"first_name":"Christian","full_name":"Meske, Christian","last_name":"Meske"},{"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","keyword":["human-agent interaction","smart homes","supervised learning","participation"],"publication":"International Conference on Human-Agent Interaction","alternative_title":["Increasing Perceived Control and Understanding"],"status":"public","date_created":"2022-12-21T09:48:43Z","_id":"34674","conference":{"name":"HAI '22: International Conference on Human-Agent Interaction","start_date":"2022-12-05","location":"Christchurch, New Zealand","end_date":"2022-12-08"},"main_file_link":[{"url":"https://papers.dice-research.org/2022/HAI_SmartHome/User_Involvement_in_Training_Smart_Home_Agents_public.pdf"}],"citation":{"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","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.","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} }","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.","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."},"type":"conference","year":"2022"},{"date_updated":"2023-06-23T09:20:20Z","_id":"33738","oa":"1","doi":"10.1007/978-3-031-11609-4_9","main_file_link":[{"open_access":"1","url":"https://2022.eswc-conferences.org/wp-content/uploads/2022/05/pd_Zahera_et_al_paper_230.pdf"}],"language":[{"iso":"eng"}],"citation":{"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} }","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.","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.","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.","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."},"year":"2022","type":"book_chapter","place":"Cham","user_id":"72768","title":"Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings","author":[{"last_name":"Zahera","id":"72768","first_name":"Hamada Mohamed Abdelsamee","orcid":"0000-0003-0215-1278","full_name":"Zahera, Hamada Mohamed Abdelsamee"},{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"last_name":"Balke","first_name":"Stefan","full_name":"Balke, Stefan"},{"last_name":"Haupt","full_name":"Haupt, Jonas","first_name":"Jonas"},{"last_name":"Voigt","first_name":"Martin","full_name":"Voigt, Martin"},{"last_name":"Walter","first_name":"Carolin","full_name":"Walter, Carolin"},{"first_name":"Fabian","full_name":"Witter, Fabian","last_name":"Witter"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"publisher":"Springer International Publishing","publication":"The Semantic Web: ESWC 2022 Satellite Events","department":[{"_id":"574"}],"status":"public","date_created":"2022-10-15T19:25:42Z","publication_status":"published","publication_identifier":{"isbn":["9783031116087","9783031116094"],"issn":["0302-9743","1611-3349"]}},{"main_file_link":[{"open_access":"1","url":"https://aclanthology.org/2022.coling-1.291.pdf"}],"language":[{"iso":"eng"}],"page":"3296–3308","type":"conference","citation":{"short":"A. Bondarenko, M. Wolska, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, B. Stein, P. Braslavski, M. Hagen, M. Potthast, in: Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, Gyeongju, Republic of Korea, 2022, pp. 3296–3308.","ieee":"A. Bondarenko et al., “CausalQA: A Benchmark for Causal Question Answering,” in Proceedings of the 29th International Conference on Computational Linguistics, 2022, pp. 3296–3308.","ama":"Bondarenko A, Wolska M, Heindorf S, et al. CausalQA: A Benchmark for Causal Question Answering. In: Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics; 2022:3296–3308.","apa":"Bondarenko, A., Wolska, M., Heindorf, S., Blübaum, L., Ngonga Ngomo, A.-C., Stein, B., Braslavski, P., Hagen, M., & Potthast, M. (2022). CausalQA: A Benchmark for Causal Question Answering. Proceedings of the 29th International Conference on Computational Linguistics, 3296–3308.","chicago":"Bondarenko, Alexander, Magdalena Wolska, Stefan Heindorf, Lukas Blübaum, Axel-Cyrille Ngonga Ngomo, Benno Stein, Pavel Braslavski, Matthias Hagen, and Martin Potthast. “CausalQA: A Benchmark for Causal Question Answering.” In Proceedings of the 29th International Conference on Computational Linguistics, 3296–3308. Gyeongju, Republic of Korea: International Committee on Computational Linguistics, 2022.","mla":"Bondarenko, Alexander, et al. “CausalQA: A Benchmark for Causal Question Answering.” Proceedings of the 29th International Conference on Computational Linguistics, International Committee on Computational Linguistics, 2022, pp. 3296–3308.","bibtex":"@inproceedings{Bondarenko_Wolska_Heindorf_Blübaum_Ngonga Ngomo_Stein_Braslavski_Hagen_Potthast_2022, place={Gyeongju, Republic of Korea}, title={CausalQA: A Benchmark for Causal Question Answering}, booktitle={Proceedings of the 29th International Conference on Computational Linguistics}, publisher={International Committee on Computational Linguistics}, author={Bondarenko, Alexander and Wolska, Magdalena and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille and Stein, Benno and Braslavski, Pavel and Hagen, Matthias and Potthast, Martin}, year={2022}, pages={3296–3308} }"},"year":"2022","_id":"33739","date_updated":"2023-07-02T18:14:01Z","oa":"1","department":[{"_id":"574"},{"_id":"760"}],"publication":"Proceedings of the 29th International Conference on Computational Linguistics","author":[{"full_name":"Bondarenko, Alexander","first_name":"Alexander","last_name":"Bondarenko"},{"last_name":"Wolska","full_name":"Wolska, Magdalena","first_name":"Magdalena"},{"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"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"},{"last_name":"Stein","full_name":"Stein, Benno","first_name":"Benno"},{"first_name":"Pavel","full_name":"Braslavski, Pavel","last_name":"Braslavski"},{"full_name":"Hagen, Matthias","first_name":"Matthias","last_name":"Hagen"},{"last_name":"Potthast","first_name":"Martin","full_name":"Potthast, Martin"}],"publisher":"International Committee on Computational Linguistics","date_created":"2022-10-15T19:33:10Z","project":[{"_id":"52","name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"status":"public","abstract":[{"text":"At least 5% of questions submitted to search engines ask about cause-effect relationships in some way. To support the development of tailored approaches that can answer such questions, we construct Webis-CausalQA-22, a benchmark corpus of 1.1 million causal questions with answers. We distinguish different types of causal questions using a novel typology derived from a data-driven, manual analysis of questions from ten large question answering (QA) datasets. Using high-precision lexical rules, we extract causal questions of each type from these datasets to create our corpus. As an initial baseline, the state-of-the-art QA model UnifiedQA achieves a ROUGE-L F1 score of 0.48 on our new benchmark.","lang":"eng"}],"place":"Gyeongju, Republic of Korea","user_id":"11871","title":"CausalQA: A Benchmark for Causal Question Answering"},{"publication":"Scientific Data","department":[{"_id":"574"}],"author":[{"full_name":"Pestryakova, Svetlana ","first_name":"Svetlana ","last_name":"Pestryakova"},{"first_name":"Daniel","full_name":"Vollmers, Daniel","last_name":"Vollmers"},{"last_name":"Sherif","id":"67234","first_name":"Mohamed","full_name":"Sherif, Mohamed","orcid":"https://orcid.org/0000-0002-9927-2203"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan"},{"last_name":"Saleem","full_name":"Saleem, Muhammad ","first_name":"Muhammad "},{"id":"71635","last_name":"Moussallem","full_name":"Moussallem, Diego","first_name":"Diego"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"date_created":"2022-02-15T16:59:29Z","status":"public","user_id":"67234","title":"CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications","main_file_link":[{"open_access":"1","url":"https://papers.dice-research.org/2022/NSDJ_CovidPubGraph/public.pdf"}],"language":[{"iso":"eng"}],"type":"journal_article","year":"2022","citation":{"chicago":"Pestryakova, Svetlana , Daniel Vollmers, Mohamed Sherif, Stefan Heindorf, Muhammad Saleem, Diego Moussallem, and Axel-Cyrille Ngonga Ngomo. “CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications.” Scientific Data, 2022.","ama":"Pestryakova S, Vollmers D, Sherif M, et al. CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications. Scientific Data. Published online 2022.","apa":"Pestryakova, S., Vollmers, D., Sherif, M., Heindorf, S., Saleem, M., Moussallem, D., & Ngonga Ngomo, A.-C. (2022). CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications. Scientific Data.","bibtex":"@article{Pestryakova_Vollmers_Sherif_Heindorf_Saleem_Moussallem_Ngonga Ngomo_2022, title={CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications}, journal={Scientific Data}, author={Pestryakova, Svetlana and Vollmers, Daniel and Sherif, Mohamed and Heindorf, Stefan and Saleem, Muhammad and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}, year={2022} }","mla":"Pestryakova, Svetlana, et al. “CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications.” Scientific Data, 2022.","short":"S. Pestryakova, D. Vollmers, M. Sherif, S. Heindorf, M. Saleem, D. Moussallem, A.-C. Ngonga Ngomo, Scientific Data (2022).","ieee":"S. Pestryakova et al., “CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications,” Scientific Data, 2022."},"_id":"29851","date_updated":"2023-08-16T10:01:49Z","oa":"1"},{"author":[{"full_name":"Deppe, Sahar","first_name":"Sahar","last_name":"Deppe"},{"full_name":"Brandt, Lukas","first_name":"Lukas","last_name":"Brandt"},{"last_name":"Brünninghaus","full_name":"Brünninghaus, Marc","first_name":"Marc"},{"last_name":"Papenkordt","id":"44648","first_name":"Jörg","full_name":"Papenkordt, Jörg"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865"},{"first_name":"Gudrun","full_name":"Tschirner-Vinke, Gudrun","last_name":"Tschirner-Vinke"}],"keyword":["Assistance system","Knowledge graph","Information retrieval","Neural networks","AR"],"department":[{"_id":"178"},{"_id":"574"},{"_id":"184"}],"status":"public","project":[{"_id":"409","grant_number":"02L19C115","name":"KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands in OstWestfalenLippe"}],"date_created":"2022-10-28T11:43:49Z","abstract":[{"lang":"eng","text":"Manufacturing companies are challenged to make the increasingly complex work processes equally manageable for all employees to prevent an impending loss of competence. In this contribution, an intelligent assistance system is proposed enabling employees to help themselves in the workplace and provide them with competence-related support. This results in increasing the short- and long-term efficiency of problem solving in companies."}],"title":"AI-Based Assistance System for Manufacturing","related_material":{"link":[{"relation":"confirmation","url":"https://ieeexplore.ieee.org/document/9921520"}]},"user_id":"44648","series_title":"2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)","type":"conference","year":"2022","citation":{"mla":"Deppe, Sahar, et al. AI-Based Assistance System for Manufacturing. 2022, doi:10.1109/ETFA52439.2022.9921520.","bibtex":"@article{Deppe_Brandt_Brünninghaus_Papenkordt_Heindorf_Tschirner-Vinke_2022, series={2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)}, title={AI-Based Assistance System for Manufacturing}, DOI={10.1109/ETFA52439.2022.9921520}, author={Deppe, Sahar and Brandt, Lukas and Brünninghaus, Marc and Papenkordt, Jörg and Heindorf, Stefan and Tschirner-Vinke, Gudrun}, year={2022}, collection={2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)} }","ama":"Deppe S, Brandt L, Brünninghaus M, Papenkordt J, Heindorf S, Tschirner-Vinke G. AI-Based Assistance System for Manufacturing. Published online 2022. doi:10.1109/ETFA52439.2022.9921520","apa":"Deppe, S., Brandt, L., Brünninghaus, M., Papenkordt, J., Heindorf, S., & Tschirner-Vinke, G. (2022). AI-Based Assistance System for Manufacturing. ETFA, Stuttgart. https://doi.org/10.1109/ETFA52439.2022.9921520","chicago":"Deppe, Sahar, Lukas Brandt, Marc Brünninghaus, Jörg Papenkordt, Stefan Heindorf, and Gudrun Tschirner-Vinke. “AI-Based Assistance System for Manufacturing.” 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA), 2022. https://doi.org/10.1109/ETFA52439.2022.9921520.","ieee":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G. Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.” 2022, doi: 10.1109/ETFA52439.2022.9921520.","short":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022)."},"language":[{"iso":"eng"}],"_id":"33957","date_updated":"2023-11-23T08:07:51Z","conference":{"end_date":"2022-09-09","name":"ETFA","start_date":"2022-09-06","location":"Stuttgart"},"doi":"10.1109/ETFA52439.2022.9921520"},{"title":"ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs","user_id":"11871","publication_status":"published","date_created":"2022-01-12T10:27:02Z","status":"public","department":[{"_id":"574"}],"publication":"Proceedings of the 11th on Knowledge Capture Conference","author":[{"full_name":"Zahera, Hamada Mohamed Abdelsamee","first_name":"Hamada Mohamed Abdelsamee","id":"72768","last_name":"Zahera"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille"}],"publisher":"ACM","doi":"10.1145/3460210.3493563","oa":"1","_id":"29291","date_updated":"2022-10-15T19:40:49Z","type":"conference","citation":{"ieee":"H. M. A. Zahera, S. Heindorf, and A.-C. Ngonga Ngomo, “ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs,” 2021, doi: 10.1145/3460210.3493563.","short":"H.M.A. Zahera, S. Heindorf, A.-C. Ngonga Ngomo, in: Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021.","bibtex":"@inproceedings{Zahera_Heindorf_Ngonga Ngomo_2021, title={ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs}, DOI={10.1145/3460210.3493563}, booktitle={Proceedings of the 11th on Knowledge Capture Conference}, publisher={ACM}, author={Zahera, Hamada Mohamed Abdelsamee and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2021} }","mla":"Zahera, Hamada Mohamed Abdelsamee, et al. “ASSET: A Semi-Supervised Approach for Entity Typing in Knowledge Graphs.” Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021, doi:10.1145/3460210.3493563.","chicago":"Zahera, Hamada Mohamed Abdelsamee, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo. “ASSET: A Semi-Supervised Approach for Entity Typing in Knowledge Graphs.” In Proceedings of the 11th on Knowledge Capture Conference. ACM, 2021. https://doi.org/10.1145/3460210.3493563.","apa":"Zahera, H. M. A., Heindorf, S., & Ngonga Ngomo, A.-C. (2021). ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs. Proceedings of the 11th on Knowledge Capture Conference. https://doi.org/10.1145/3460210.3493563","ama":"Zahera HMA, Heindorf S, Ngonga Ngomo A-C. ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs. In: Proceedings of the 11th on Knowledge Capture Conference. ACM; 2021. doi:10.1145/3460210.3493563"},"year":"2021","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://papers.dice-research.org/2021/KCAP2021_ASSET/public.pdf","open_access":"1"}]},{"oa":"1","doi":"10.1007/978-3-030-91608-4_11","date_updated":"2022-10-15T19:54:20Z","language":[{"iso":"eng"}],"related_material":{"link":[{"relation":"confirmation","url":"https://link.springer.com/chapter/10.1007/978-3-030-91608-4_11"}]},"title":"Drift Detection in Text Data with Document Embeddings","place":"Cham","publication_status":"published","publication_identifier":{"isbn":["9783030916077","9783030916084"],"issn":["0302-9743","1611-3349"]},"department":[{"_id":"574"}],"_id":"29292","year":"2021","citation":{"mla":"Feldhans, Robert, et al. “Drift Detection in Text Data with Document Embeddings.” Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, 2021, doi:10.1007/978-3-030-91608-4_11.","bibtex":"@inbook{Feldhans_Wilke_Heindorf_Shaker_Hammer_Ngonga Ngomo_Hüllermeier_2021, place={Cham}, title={Drift Detection in Text Data with Document Embeddings}, DOI={10.1007/978-3-030-91608-4_11}, booktitle={Intelligent Data Engineering and Automated Learning – IDEAL 2021}, publisher={Springer International Publishing}, author={Feldhans, Robert and Wilke, Adrian and Heindorf, Stefan and Shaker, Mohammad Hossein and Hammer, Barbara and Ngonga Ngomo, Axel-Cyrille and Hüllermeier, Eyke}, year={2021} }","apa":"Feldhans, R., Wilke, A., Heindorf, S., Shaker, M. H., Hammer, B., Ngonga Ngomo, A.-C., & Hüllermeier, E. (2021). Drift Detection in Text Data with Document Embeddings. In Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer International Publishing. https://doi.org/10.1007/978-3-030-91608-4_11","ama":"Feldhans R, Wilke A, Heindorf S, et al. Drift Detection in Text Data with Document Embeddings. In: Intelligent Data Engineering and Automated Learning – IDEAL 2021. Springer International Publishing; 2021. doi:10.1007/978-3-030-91608-4_11","chicago":"Feldhans, Robert, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker, Barbara Hammer, Axel-Cyrille Ngonga Ngomo, and Eyke Hüllermeier. “Drift Detection in Text Data with Document Embeddings.” In Intelligent Data Engineering and Automated Learning – IDEAL 2021. Cham: Springer International Publishing, 2021. https://doi.org/10.1007/978-3-030-91608-4_11.","ieee":"R. Feldhans et al., “Drift Detection in Text Data with Document Embeddings,” in Intelligent Data Engineering and Automated Learning – IDEAL 2021, Cham: Springer International Publishing, 2021.","short":"R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021."},"type":"book_chapter","main_file_link":[{"url":"https://papers.dice-research.org/2021/IDEAL2021_DriftDetectionEmbeddings/Drift-Detection-in-Text-Data-with-Document-Embeddings-public.pdf","open_access":"1"}],"user_id":"11871","date_created":"2022-01-12T10:27:23Z","status":"public","publication":"Intelligent Data Engineering and Automated Learning – IDEAL 2021","publisher":"Springer International Publishing","author":[{"first_name":"Robert","full_name":"Feldhans, Robert","last_name":"Feldhans"},{"id":"9101","last_name":"Wilke","orcid":"0000-0002-6575-807X","full_name":"Wilke, Adrian","first_name":"Adrian"},{"first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871"},{"last_name":"Shaker","first_name":"Mohammad Hossein","full_name":"Shaker, Mohammad Hossein"},{"last_name":"Hammer","first_name":"Barbara","full_name":"Hammer, Barbara"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"},{"last_name":"Hüllermeier","id":"48129","first_name":"Eyke","full_name":"Hüllermeier, Eyke"}]},{"abstract":[{"text":"Knowledge graph embedding research has mainly focused on the two smallest\r\nnormed division algebras, $\\mathbb{R}$ and $\\mathbb{C}$. Recent results suggest\r\nthat trilinear products of quaternion-valued embeddings can be a more effective\r\nmeans to tackle link prediction. In addition, models based on convolutions on\r\nreal-valued embeddings often yield state-of-the-art results for link\r\nprediction. In this paper, we investigate a composition of convolution\r\noperations with hypercomplex multiplications. We propose the four approaches\r\nQMult, OMult, ConvQ and ConvO to tackle the link prediction problem. QMult and\r\nOMult can be considered as quaternion and octonion extensions of previous\r\nstate-of-the-art approaches, including DistMult and ComplEx. ConvQ and ConvO\r\nbuild upon QMult and OMult by including convolution operations in a way\r\ninspired by the residual learning framework. We evaluated our approaches on\r\nseven link prediction datasets including WN18RR, FB15K-237 and YAGO3-10.\r\nExperimental results suggest that the benefits of learning hypercomplex-valued\r\nvector representations become more apparent as the size and complexity of the\r\nknowledge graph grows. ConvO outperforms state-of-the-art approaches on\r\nFB15K-237 in MRR, Hit@1 and Hit@3, while QMult, OMult, ConvQ and ConvO\r\noutperform state-of-the-approaches on YAGO3-10 in all metrics. Results also\r\nsuggest that link prediction performances can be further improved via\r\nprediction averaging. To foster reproducible research, we provide an\r\nopen-source implementation of approaches, including training and evaluation\r\nscripts as well as pretrained models.","lang":"eng"}],"external_id":{"arxiv":["2106.15230"]},"user_id":"11871","title":"Convolutional Hypercomplex Embeddings for Link Prediction","publication":"The 13th Asian Conference on Machine Learning, ACML 2021","department":[{"_id":"574"}],"author":[{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"id":"71635","last_name":"Moussallem","full_name":"Moussallem, Diego","first_name":"Diego"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"first_name":"Axel-Cyrille","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","id":"65716"}],"date_created":"2022-01-12T10:21:10Z","status":"public","_id":"29287","date_updated":"2022-10-17T15:06:40Z","oa":"1","main_file_link":[{"url":"https://papers.dice-research.org/2021/ACML2021_HyperConv/public.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"type":"conference","citation":{"ieee":"C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional Hypercomplex Embeddings for Link Prediction,” 2021.","short":"C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021.","bibtex":"@inproceedings{Demir_Moussallem_Heindorf_Ngonga Ngomo_2021, title={Convolutional Hypercomplex Embeddings for Link Prediction}, booktitle={The 13th Asian Conference on Machine Learning, ACML 2021}, author={Demir, Caglar and Moussallem, Diego and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2021} }","mla":"Demir, Caglar, et al. “Convolutional Hypercomplex Embeddings for Link Prediction.” The 13th Asian Conference on Machine Learning, ACML 2021, 2021.","apa":"Demir, C., Moussallem, D., Heindorf, S., & Ngonga Ngomo, A.-C. (2021). Convolutional Hypercomplex Embeddings for Link Prediction. The 13th Asian Conference on Machine Learning, ACML 2021.","ama":"Demir C, Moussallem D, Heindorf S, Ngonga Ngomo A-C. Convolutional Hypercomplex Embeddings for Link Prediction. In: The 13th Asian Conference on Machine Learning, ACML 2021. ; 2021.","chicago":"Demir, Caglar, Diego Moussallem, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo. “Convolutional Hypercomplex Embeddings for Link Prediction.” In The 13th Asian Conference on Machine Learning, ACML 2021, 2021."},"year":"2021"},{"language":[{"iso":"eng"}],"type":"conference","citation":{"bibtex":"@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={10.1109/wacv48630.2021.00204}, booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)}, publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor}, year={2021} }","mla":"Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021, doi:10.1109/wacv48630.2021.00204.","apa":"Nickchen, T., Heindorf, S., & Engels, G. (2021). Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). https://doi.org/10.1109/wacv48630.2021.00204","ama":"Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. In: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE; 2021. doi:10.1109/wacv48630.2021.00204","chicago":"Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” In 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2021. https://doi.org/10.1109/wacv48630.2021.00204.","ieee":"T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: 10.1109/wacv48630.2021.00204.","short":"T. Nickchen, S. 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Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, and M. Potthast, “CauseNet: Towards a Causality Graph Extracted from the Web,” in Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030, doi: 10.1145/3340531.3412763.","short":"S. Heindorf, Y. Scholten, H. Wachsmuth, A.-C. Ngonga Ngomo, M. Potthast, in: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–3030.","mla":"Heindorf, Stefan, et al. “CauseNet: Towards a Causality Graph Extracted from the Web.” Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 2020, pp. 3023–30, doi:10.1145/3340531.3412763.","bibtex":"@inproceedings{Heindorf_Scholten_Wachsmuth_Ngonga Ngomo_Potthast_2020, title={CauseNet: Towards a Causality Graph Extracted from the Web}, DOI={10.1145/3340531.3412763}, booktitle={Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020)}, author={Heindorf, Stefan and Scholten, Yan and Wachsmuth, Henning and Ngonga Ngomo, Axel-Cyrille and Potthast, Martin}, year={2020}, pages={3023–3030} }","ama":"Heindorf S, Scholten Y, Wachsmuth H, Ngonga Ngomo A-C, Potthast M. CauseNet: Towards a Causality Graph Extracted from the Web. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020). ; 2020:3023-3030. doi:10.1145/3340531.3412763","apa":"Heindorf, S., Scholten, Y., Wachsmuth, H., Ngonga Ngomo, A.-C., & Potthast, M. (2020). CauseNet: Towards a Causality Graph Extracted from the Web. 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Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn, 2019.","ama":"Heindorf S. Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn; 2019.","apa":"Heindorf, S. (2019). Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn.","bibtex":"@book{Heindorf_2019, title={Vandalism Detection in Crowdsourced Knowledge Bases}, publisher={Universität Paderborn}, author={Heindorf, Stefan}, year={2019} }","mla":"Heindorf, Stefan. Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn, 2019.","short":"S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases, Universität Paderborn, 2019.","ieee":"S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases. 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Heindorf, Y. Scholten, G. Engels, and M. Potthast, “Debiasing Vandalism Detection Models at Wikidata (Extended Abstract),” in INFORMATIK, 2019, pp. 289–290.","short":"S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: INFORMATIK, 2019, pp. 289–290.","bibtex":"@inproceedings{Heindorf_Scholten_Engels_Potthast_2019, title={Debiasing Vandalism Detection Models at Wikidata (Extended Abstract)}, DOI={10.18420/inf2019_48}, booktitle={INFORMATIK}, author={Heindorf, Stefan and Scholten, Yan and Engels, Gregor and Potthast, Martin}, year={2019}, pages={289–290} }","mla":"Heindorf, Stefan, et al. “Debiasing Vandalism Detection Models at Wikidata (Extended Abstract).” INFORMATIK, 2019, pp. 289–90, doi:10.18420/inf2019_48.","ama":"Heindorf S, Scholten Y, Engels G, Potthast M. Debiasing Vandalism Detection Models at Wikidata (Extended Abstract). In: INFORMATIK. ; 2019:289-290. doi:10.18420/inf2019_48","apa":"Heindorf, S., Scholten, Y., Engels, G., & Potthast, M. (2019). Debiasing Vandalism Detection Models at Wikidata (Extended Abstract). In INFORMATIK (pp. 289–290). https://doi.org/10.18420/inf2019_48","chicago":"Heindorf, Stefan, Yan Scholten, Gregor Engels, and Martin Potthast. “Debiasing Vandalism Detection Models at Wikidata (Extended Abstract).” In INFORMATIK, 289–90, 2019. https://doi.org/10.18420/inf2019_48."},"year":"2019","type":"conference","page":"289-290","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://dl.gi.de/bitstream/handle/20.500.12116/24997/paper3_25.pdf"}],"title":"Debiasing Vandalism Detection Models at Wikidata (Extended Abstract)","user_id":"11871","status":"public","date_created":"2019-11-05T15:48:52Z","author":[{"first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871"},{"last_name":"Scholten","first_name":"Yan","full_name":"Scholten, Yan"},{"id":"107","last_name":"Engels","full_name":"Engels, Gregor","first_name":"Gregor"},{"first_name":"Martin","full_name":"Potthast, Martin","last_name":"Potthast"}],"department":[{"_id":"66"}],"publication":"INFORMATIK"},{"title":"Semantic Data Mediator: Linking Services to Websites","place":"Cham","publication_identifier":{"isbn":["978-3-319-91764-1"]},"editor":[{"first_name":"Lars","full_name":"Braubach, Lars","last_name":"Braubach"},{"full_name":"Murillo, Juan M.","first_name":"Juan M.","last_name":"Murillo"},{"last_name":"Kaviani","full_name":"Kaviani, Nima","first_name":"Nima"},{"last_name":"Lama","full_name":"Lama, Manuel","first_name":"Manuel"},{"last_name":"Burgueño","full_name":"Burgueño, Loli","first_name":"Loli"},{"first_name":"Naouel","full_name":"Moha, Naouel","last_name":"Moha"},{"last_name":"Oriol","full_name":"Oriol, Marc","first_name":"Marc"}],"department":[{"_id":"66"}],"oa":"1","doi":"10.1007/978-3-319-91764-1_36","date_updated":"2022-10-15T20:00:17Z","language":[{"iso":"eng"}],"user_id":"11871","abstract":[{"lang":"eng","text":"Many websites offer links to social media sites for convenient content sharing. Unfortunately, those sharing capabilities are quite restricted and it is seldom possible to share content with other services, like those provided by a user's favorite applications or smart devices. In this paper, we present Semantic Data Mediator (SDM) --- a flexible middleware linking a vast number of services to millions of websites. Based on reusable repositories of service descriptions defined by the crowd, users can easily fill a personal registry with their favorite services, which can then be linked to websites by SDM. For this, SDM leverages semantic data, which is already available on millions of websites due to search engine optimization. Further support for our approach from website or service developers is not required. To enable the use of a broad range of services, data conversion services are automatically composed by SDM to transform data according to the needs of the different services. In addition to linking web services, various service adapters allow services of applications and smart devices to be linked as well. We have fully implemented our approach and present a real-world case study demonstrating its feasibility and usefulness."}],"date_created":"2018-11-26T11:52:59Z","status":"public","publication":"Service-Oriented Computing -- ICSOC 2017 Workshops","publisher":"Springer International Publishing","author":[{"id":"11308","last_name":"Wolters","full_name":"Wolters, Dennis","first_name":"Dennis"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865"},{"id":"39928","last_name":"Kirchhoff","full_name":"Kirchhoff, Jonas","first_name":"Jonas"},{"last_name":"Engels","id":"107","first_name":"Gregor","full_name":"Engels, Gregor"}],"_id":"5831","page":"388-392","citation":{"ieee":"D. Wolters, S. Heindorf, J. Kirchhoff, and G. Engels, “Semantic Data Mediator: Linking Services to Websites,” in Service-Oriented Computing -- ICSOC 2017 Workshops, 2018, pp. 388–392, doi: 10.1007/978-3-319-91764-1_36.","short":"D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: L. Braubach, J.M. Murillo, N. Kaviani, M. Lama, L. Burgueño, N. Moha, M. Oriol (Eds.), Service-Oriented Computing -- ICSOC 2017 Workshops, Springer International Publishing, Cham, 2018, pp. 388–392.","mla":"Wolters, Dennis, et al. “Semantic Data Mediator: Linking Services to Websites.” Service-Oriented Computing -- ICSOC 2017 Workshops, edited by Lars Braubach et al., Springer International Publishing, 2018, pp. 388–92, doi:10.1007/978-3-319-91764-1_36.","bibtex":"@inproceedings{Wolters_Heindorf_Kirchhoff_Engels_2018, place={Cham}, title={Semantic Data Mediator: Linking Services to Websites}, DOI={10.1007/978-3-319-91764-1_36}, booktitle={Service-Oriented Computing -- ICSOC 2017 Workshops}, publisher={Springer International Publishing}, author={Wolters, Dennis and Heindorf, Stefan and Kirchhoff, Jonas and Engels, Gregor}, editor={Braubach, Lars and Murillo, Juan M. and Kaviani, Nima and Lama, Manuel and Burgueño, Loli and Moha, Naouel and Oriol, Marc}, year={2018}, pages={388–392} }","apa":"Wolters, D., Heindorf, S., Kirchhoff, J., & Engels, G. (2018). Semantic Data Mediator: Linking Services to Websites. In L. Braubach, J. M. Murillo, N. Kaviani, M. Lama, L. Burgueño, N. Moha, & M. Oriol (Eds.), Service-Oriented Computing -- ICSOC 2017 Workshops (pp. 388–392). Springer International Publishing. https://doi.org/10.1007/978-3-319-91764-1_36","ama":"Wolters D, Heindorf S, Kirchhoff J, Engels G. Semantic Data Mediator: Linking Services to Websites. In: Braubach L, Murillo JM, Kaviani N, et al., eds. Service-Oriented Computing -- ICSOC 2017 Workshops. Springer International Publishing; 2018:388-392. doi:10.1007/978-3-319-91764-1_36","chicago":"Wolters, Dennis, Stefan Heindorf, Jonas Kirchhoff, and Gregor Engels. “Semantic Data Mediator: Linking Services to Websites.” In Service-Oriented Computing -- ICSOC 2017 Workshops, edited by Lars Braubach, Juan M. Murillo, Nima Kaviani, Manuel Lama, Loli Burgueño, Naouel Moha, and Marc Oriol, 388–92. Cham: Springer International Publishing, 2018. https://doi.org/10.1007/978-3-319-91764-1_36."},"type":"conference","year":"2018","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/wolters2017_ICSOC_demo.pdf"}]},{"title":"WSDM Cup 2017: Vandalism Detection and Triple Scoring","user_id":"11871","status":"public","date_created":"2019-01-15T08:54:23Z","publisher":"ACM","author":[{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"last_name":"Potthast","first_name":"Martin","full_name":"Potthast, Martin"},{"last_name":"Bast","first_name":"Hannah","full_name":"Bast, Hannah"},{"last_name":"Buchhold","full_name":"Buchhold, Björn","first_name":"Björn"},{"full_name":"Haussmann, Elmar","first_name":"Elmar","last_name":"Haussmann"}],"department":[{"_id":"66"}],"publication":"WSDM","oa":"1","date_updated":"2022-01-06T07:03:17Z","_id":"6721","type":"conference","year":"2017","citation":{"ieee":"S. Heindorf, M. Potthast, H. Bast, B. Buchhold, and E. Haussmann, “WSDM Cup 2017: Vandalism Detection and Triple Scoring,” in WSDM, 2017, pp. 827–828.","short":"S. Heindorf, M. Potthast, H. Bast, B. Buchhold, E. Haussmann, in: WSDM, ACM, 2017, pp. 827–828.","mla":"Heindorf, Stefan, et al. “WSDM Cup 2017: Vandalism Detection and Triple Scoring.” WSDM, ACM, 2017, pp. 827–28.","bibtex":"@inproceedings{Heindorf_Potthast_Bast_Buchhold_Haussmann_2017, title={WSDM Cup 2017: Vandalism Detection and Triple Scoring}, booktitle={WSDM}, publisher={ACM}, author={Heindorf, Stefan and Potthast, Martin and Bast, Hannah and Buchhold, Björn and Haussmann, Elmar}, year={2017}, pages={827–828} }","chicago":"Heindorf, Stefan, Martin Potthast, Hannah Bast, Björn Buchhold, and Elmar Haussmann. “WSDM Cup 2017: Vandalism Detection and Triple Scoring.” In WSDM, 827–28. ACM, 2017.","ama":"Heindorf S, Potthast M, Bast H, Buchhold B, Haussmann E. WSDM Cup 2017: Vandalism Detection and Triple Scoring. In: WSDM. ACM; 2017:827-828.","apa":"Heindorf, S., Potthast, M., Bast, H., Buchhold, B., & Haussmann, E. (2017). WSDM Cup 2017: Vandalism Detection and Triple Scoring. In WSDM (pp. 827–828). ACM."},"page":"827-828","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/heindorf2017_WSDM.pdf"}]},{"publication_status":"published","publication_identifier":{"isbn":["9781538607527"]},"editor":[{"last_name":"Altintas","first_name":"Ilkay","full_name":"Altintas, Ilkay"},{"full_name":"Chen, Shiping","first_name":"Shiping","last_name":"Chen"}],"department":[{"_id":"66"}],"title":"Linking Services to Websites by Leveraging Semantic Data","language":[{"iso":"eng"}],"oa":"1","doi":"10.1109/icws.2017.80","date_updated":"2022-10-15T20:01:55Z","date_created":"2018-11-26T11:49:31Z","status":"public","keyword":["Services","Websites","Semantic Data","schema.org","Data Conversion","Interface Adaptation","Mediation"],"publication":"2017 IEEE International Conference on Web Services (ICWS)","author":[{"first_name":"Dennis","full_name":"Wolters, Dennis","last_name":"Wolters","id":"11308"},{"last_name":"Heindorf","id":"11871","first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan"},{"first_name":"Jonas","full_name":"Kirchhoff, Jonas","last_name":"Kirchhoff","id":"39928"},{"first_name":"Gregor","full_name":"Engels, Gregor","last_name":"Engels","id":"107"}],"publisher":"IEEE","user_id":"11871","abstract":[{"text":"Websites increasingly embed semantic data for search engine optimization. The most common ontology for semantic data, schema.org, is supported by all major search engines and describes over 500 data types, including calendar events, recipes, products, and TV shows. As of today, users wishing to pass this data to their favorite applications, e.g., their calendars, cookbooks, price comparison applications or even smart devices such as TV receivers, rely on cumbersome and error-prone workarounds such as reentering the data or a series of copy and paste operations. In this paper, we present Semantic Data Mediator (SDM), an approach that allows the easy transfer of semantic data to a multitude of services, ranging from web services to applications installed on different devices. SDM extracts semantic data from the currently displayed web page on the client-side, offers suitable services to the user, and by the press of a button, forwards this data to the desired service while doing all the necessary data conversion and service interface adaptation in between. To realize this, we built a reusable repository of service descriptions, data converters, and service adapters, which can be extended by the crowd. Our approach for linking services to websites relies solely on semantic data and does not require any additional support by either website or service developers. We have fully implemented our approach and present a real-world case study demonstrating its feasibility and usefulness.","lang":"eng"}],"citation":{"ama":"Wolters D, Heindorf S, Kirchhoff J, Engels G. Linking Services to Websites by Leveraging Semantic Data. In: Altintas I, Chen S, eds. 2017 IEEE International Conference on Web Services (ICWS). IEEE; 2017. doi:10.1109/icws.2017.80","apa":"Wolters, D., Heindorf, S., Kirchhoff, J., & Engels, G. (2017). Linking Services to Websites by Leveraging Semantic Data. In I. Altintas & S. Chen (Eds.), 2017 IEEE International Conference on Web Services (ICWS). IEEE. https://doi.org/10.1109/icws.2017.80","chicago":"Wolters, Dennis, Stefan Heindorf, Jonas Kirchhoff, and Gregor Engels. “Linking Services to Websites by Leveraging Semantic Data.” In 2017 IEEE International Conference on Web Services (ICWS), edited by Ilkay Altintas and Shiping Chen. IEEE, 2017. https://doi.org/10.1109/icws.2017.80.","mla":"Wolters, Dennis, et al. “Linking Services to Websites by Leveraging Semantic Data.” 2017 IEEE International Conference on Web Services (ICWS), edited by Ilkay Altintas and Shiping Chen, IEEE, 2017, doi:10.1109/icws.2017.80.","bibtex":"@inproceedings{Wolters_Heindorf_Kirchhoff_Engels_2017, title={Linking Services to Websites by Leveraging Semantic Data}, DOI={10.1109/icws.2017.80}, booktitle={2017 IEEE International Conference on Web Services (ICWS)}, publisher={IEEE}, author={Wolters, Dennis and Heindorf, Stefan and Kirchhoff, Jonas and Engels, Gregor}, editor={Altintas, Ilkay and Chen, Shiping}, year={2017} }","short":"D. Wolters, S. Heindorf, J. Kirchhoff, G. Engels, in: I. Altintas, S. Chen (Eds.), 2017 IEEE International Conference on Web Services (ICWS), IEEE, 2017.","ieee":"D. Wolters, S. Heindorf, J. Kirchhoff, and G. Engels, “Linking Services to Websites by Leveraging Semantic Data,” in 2017 IEEE International Conference on Web Services (ICWS), 2017, doi: 10.1109/icws.2017.80."},"type":"conference","year":"2017","main_file_link":[{"open_access":"1","url":"https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/wolters2017_ICWS.pdf"}],"_id":"5829"},{"date_updated":"2022-10-17T11:36:12Z","_id":"6722","oa":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1712.05956"}],"language":[{"iso":"eng"}],"type":"conference","citation":{"apa":"Heindorf, S., Potthast, M., Engels, G., & Stein, B. (2017). Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017. WSDM Cup 2017 Notebook Papers.","ama":"Heindorf S, Potthast M, Engels G, Stein B. Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017. In: WSDM Cup 2017 Notebook Papers. ; 2017.","chicago":"Heindorf, Stefan, Martin Potthast, Gregor Engels, and Benno Stein. “Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017.” In WSDM Cup 2017 Notebook Papers, 2017.","bibtex":"@inproceedings{Heindorf_Potthast_Engels_Stein_2017, title={Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017}, booktitle={WSDM Cup 2017 Notebook Papers}, author={Heindorf, Stefan and Potthast, Martin and Engels, Gregor and Stein, Benno}, year={2017} }","mla":"Heindorf, Stefan, et al. “Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017.” WSDM Cup 2017 Notebook Papers, 2017.","short":"S. Heindorf, M. Potthast, G. Engels, B. Stein, in: WSDM Cup 2017 Notebook Papers, 2017.","ieee":"S. Heindorf, M. Potthast, G. Engels, and B. Stein, “Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017,” 2017."},"year":"2017","abstract":[{"text":"We report on the Wikidata vandalism detection task at the WSDM Cup 2017. The\r\ntask received five submissions for which this paper describes their evaluation\r\nand a comparison to state of the art baselines. Unlike previous work, we recast\r\nWikidata vandalism detection as an online learning problem, requiring\r\nparticipant software to predict vandalism in near real-time. The\r\nbest-performing approach achieves a ROC-AUC of 0.947 at a PR-AUC of 0.458. In\r\nparticular, this task was organized as a software submission task: to maximize\r\nreproducibility as well as to foster future research and development on this\r\ntask, the participants were asked to submit their working software to the TIRA\r\nexperimentation platform along with the source code for open source release.","lang":"eng"}],"user_id":"11871","title":"Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017","publication":"WSDM Cup 2017 Notebook Papers","department":[{"_id":"66"}],"author":[{"first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","last_name":"Heindorf","id":"11871"},{"full_name":"Potthast, Martin","first_name":"Martin","last_name":"Potthast"},{"id":"107","last_name":"Engels","full_name":"Engels, Gregor","first_name":"Gregor"},{"full_name":"Stein, Benno","first_name":"Benno","last_name":"Stein"}],"date_created":"2019-01-15T08:57:40Z","status":"public"},{"date_created":"2022-10-15T19:14:01Z","status":"public","publication":"arXiv:1712.09528","department":[{"_id":"66"}],"author":[{"first_name":"Martin","full_name":"Potthast, Martin","last_name":"Potthast"},{"id":"11871","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan"},{"full_name":"Bast, Hannah","first_name":"Hannah","last_name":"Bast"}],"user_id":"11871","title":"Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring","abstract":[{"text":"The WSDM Cup 2017 was a data mining challenge held in conjunction with the\r\n10th International Conference on Web Search and Data Mining (WSDM). It\r\naddressed key challenges of knowledge bases today: quality assurance and entity\r\nsearch. For quality assurance, we tackle the task of vandalism detection, based\r\non a dataset of more than 82 million user-contributed revisions of the Wikidata\r\nknowledge base, all of which annotated with regard to whether or not they are\r\nvandalism. For entity search, we tackle the task of triple scoring, using a\r\ndataset that comprises relevance scores for triples from type-like relations\r\nincluding occupation and country of citizenship, based on about 10,000 human\r\nrelevance judgements. For reproducibility sake, participants were asked to\r\nsubmit their software on TIRA, a cloud-based evaluation platform, and they were\r\nincentivized to share their approaches open source.","lang":"eng"}],"external_id":{"arxiv":["1712.09528"]},"language":[{"iso":"eng"}],"year":"2017","citation":{"ieee":"M. Potthast, S. Heindorf, and H. Bast, “Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring,” arXiv:1712.09528. 2017.","short":"M. Potthast, S. Heindorf, H. Bast, ArXiv:1712.09528 (2017).","bibtex":"@article{Potthast_Heindorf_Bast_2017, title={Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring}, journal={arXiv:1712.09528}, author={Potthast, Martin and Heindorf, Stefan and Bast, Hannah}, year={2017} }","mla":"Potthast, Martin, et al. “Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring.” ArXiv:1712.09528, 2017.","chicago":"Potthast, Martin, Stefan Heindorf, and Hannah Bast. “Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring.” ArXiv:1712.09528, 2017.","ama":"Potthast M, Heindorf S, Bast H. Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring. arXiv:171209528. Published online 2017.","apa":"Potthast, M., Heindorf, S., & Bast, H. (2017). Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring. In arXiv:1712.09528."},"type":"preprint","date_updated":"2022-10-17T11:21:00Z","_id":"33732"},{"title":"Vandalism Detection in Wikidata","department":[{"_id":"66"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"17","name":"SFB 901 - Subprojekt C5"},{"name":"SFB 901 - Project Area C","_id":"4"}],"date_updated":"2022-10-17T11:31:41Z","oa":"1","doi":"10.1145/2983323.2983740","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Wikidata is the new, large-scale knowledge base of the Wikimedia Foundation. Its knowledge is increasingly used within Wikipedia itself and various other kinds of information systems, imposing high demands on its integrity.Wikidata can be edited by anyone and, unfortunately, it frequently gets vandalized, exposing all information systems using it to the risk of spreading vandalized and falsified information. In this paper, we present a new machine learning-based approach to detect vandalism in Wikidata.We propose a set of 47 features that exploit both content and context information, and we report on 4 classifiers of increasing effectiveness tailored to this learning task. Our approach is evaluated on the recently published Wikidata Vandalism Corpus WDVC-2015 and it achieves an area under curve value of the receiver operating characteristic, ROC-AUC, of 0.991. It significantly outperforms the state of the art represented by the rule-based Wikidata Abuse Filter (0.865 ROC-AUC) and a prototypical vandalism detector recently introduced by Wikimedia within the Objective Revision Evaluation Service (0.859 ROC-AUC)."}],"user_id":"11871","ddc":["040"],"file":[{"date_created":"2018-03-21T13:01:43Z","file_name":"137-p327-heindorf.pdf","access_level":"closed","file_id":"1561","creator":"florida","file_size":1842753,"success":1,"relation":"main_file","date_updated":"2018-03-21T13:01:43Z","content_type":"application/pdf"}],"author":[{"orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","first_name":"Stefan","id":"11871","last_name":"Heindorf"},{"last_name":"Potthast","first_name":"Matthias","full_name":"Potthast, Matthias"},{"first_name":"Benno","full_name":"Stein, Benno","last_name":"Stein"},{"full_name":"Engels, Gregor","first_name":"Gregor","id":"107","last_name":"Engels"}],"file_date_updated":"2018-03-21T13:01:43Z","publication":"Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016)","has_accepted_license":"1","status":"public","date_created":"2017-10-17T12:41:18Z","_id":"137","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2016_CIKM.pdf"}],"citation":{"ama":"Heindorf S, Potthast M, Stein B, Engels G. 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