--- _id: '33734' 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' author: - first_name: N'Dah Jean full_name: KOUAGOU, N'Dah Jean id: '87189' last_name: KOUAGOU - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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 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} }' 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. 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.' 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. 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.' conference: end_date: 2023-06-01 location: Hersonissos, Crete, Greece name: 20th Extended Semantic Web Conference start_date: 2023-05-28 date_created: 2022-10-15T19:20:11Z date_updated: 2023-07-02T18:10:02Z department: - _id: '574' - _id: '760' doi: https://doi.org/10.1007/978-3-031-33455-9_13 editor: - first_name: Catia full_name: Pesquita, 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 - first_name: Mauro full_name: Dragoni, Mauro last_name: Dragoni - 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 external_id: unknown: - https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13 intvolume: ' 13870' keyword: - Neural network - Concept learning - Description logics language: - iso: eng main_file_link: - open_access: '1' url: https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf oa: '1' page: 209 - 226 project: - _id: '410' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' - _id: '407' grant_number: '101070305' name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs' - _id: '285' grant_number: NW21-059D name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems' publication: The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) publication_identifier: unknown: - 978-3-031-33455-9 publication_status: published publisher: Springer International Publishing status: public title: Neural Class Expression Synthesis type: conference user_id: '11871' volume: 13870 year: '2023' ... --- _id: '37937' 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." author: - first_name: Leonie Nora full_name: Sieger, Leonie Nora id: '93402' last_name: Sieger - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Lukas full_name: Blübaum, Lukas last_name: Blübaum - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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. 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} }' 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. mla: Sieger, Leonie Nora, et al. “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). date_created: 2023-01-22T19:36:01Z date_updated: 2023-07-02T18:10:34Z department: - _id: '574' - _id: '760' external_id: arxiv: - '2301.05109' language: - iso: eng main_file_link: - url: https://arxiv.org/pdf/2301.05109.pdf publication: arXiv:2301.05109 status: public title: Counterfactual Explanations for Concepts in ELH type: preprint user_id: '11871' year: '2023' ... --- _id: '46575' author: - first_name: Alkid full_name: Baci, Alkid last_name: Baci - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 citation: 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. 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. ieee: A. Baci and S. Heindorf, “Accelerating Concept Learning via Sampling,” 2023. mla: Baci, Alkid, and Stefan Heindorf. “Accelerating Concept Learning via Sampling.” CIKM, 2023. short: 'A. Baci, S. Heindorf, in: CIKM, 2023.' date_created: 2023-08-19T08:02:54Z date_updated: 2023-08-19T08:08:53Z ddc: - '000' department: - _id: '760' file: - access_level: open_access content_type: application/pdf creator: heindorf date_created: 2023-08-19T08:08:39Z date_updated: 2023-08-19T08:08:39Z file_id: '46577' file_name: baci2023_CIKM.pdf file_size: 523067 relation: main_file file_date_updated: 2023-08-19T08:08:39Z has_accepted_license: '1' language: - iso: eng oa: '1' publication: CIKM status: public title: Accelerating Concept Learning via Sampling type: conference user_id: '11871' year: '2023' ... --- _id: '47421' abstract: - lang: eng 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. author: - first_name: N'Dah Jean full_name: Kouagou, N'Dah Jean id: '87189' last_name: Kouagou - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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' 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} }' 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.' 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.' 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.' conference: end_date: 2023-09-22 location: Turin name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases start_date: 2023-09-18 date_created: 2023-09-25T13:42:01Z date_updated: 2023-11-21T09:20:31Z department: - _id: '760' - _id: '574' doi: 10.1007/978-3-031-43421-1_12 language: - iso: eng place: Cham publication: 'Machine Learning and Knowledge Discovery in Databases: Research Track' publication_identifier: isbn: - '9783031434204' - '9783031434211' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Neural Class Expression Synthesis in ALCHIQ(D) type: book_chapter user_id: '11871' year: '2023' ... --- _id: '46460' author: - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: N'Dah Jean full_name: Kouagou, N'Dah Jean id: '87189' last_name: Kouagou - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Nikoloas full_name: Karalis, Nikoloas last_name: Karalis - first_name: Alexander full_name: Bigerl, Alexander id: '72857' last_name: Bigerl citation: 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. 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} }' 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. 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. mla: Ngonga Ngomo, Axel-Cyrille, et al. “Class Expression Learning with Multiple Representations.” 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.' date_created: 2023-08-08T11:49:51Z date_updated: 2023-11-21T08:06:20Z department: - _id: '760' - _id: '574' language: - iso: eng page: 272–286 publication: Compendium of Neurosymbolic Artificial Intelligence publisher: IOS Press status: public title: Class Expression Learning with Multiple Representations type: book_chapter user_id: '14931' year: '2023' ... --- _id: '46248' author: - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Michel full_name: Wiebesiek, Michel last_name: Wiebesiek - first_name: Renzhong full_name: Lu, Renzhong last_name: Lu - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 citation: 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} }' 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.' 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.' mla: 'Demir, Caglar, et al. “LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals.” ECML PKDD, 2023.' short: C. Demir, M. Wiebesiek, R. Lu, A.-C. Ngonga Ngomo, S. Heindorf, ECML PKDD (2023). conference: location: Torino name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases date_created: 2023-08-01T09:24:21Z date_updated: 2024-03-06T16:18:53Z ddc: - '000' department: - _id: '574' - _id: '760' file: - access_level: open_access content_type: application/pdf creator: cdemir date_created: 2023-08-01T09:24:15Z date_updated: 2023-08-01T09:24:15Z file_id: '46249' file_name: public.pdf file_size: 562759 relation: main_file file_date_updated: 2023-08-01T09:24:15Z has_accepted_license: '1' language: - iso: eng oa: '1' project: - _id: '407' grant_number: '101070305' name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs' - _id: '410' grant_number: '860801' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' - _id: '285' grant_number: NW21-059D name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems' publication: ECML PKDD status: public title: 'LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals' type: journal_article user_id: '14931' year: '2023' ... --- _id: '33740' author: - first_name: N'Dah Jean full_name: KOUAGOU, N'Dah Jean id: '87189' last_name: KOUAGOU - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo 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 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} }' 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.' 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.' 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.' date_created: 2022-10-15T19:34:41Z date_updated: 2022-10-15T19:52:08Z department: - _id: '574' doi: 10.1007/978-3-031-06981-9_14 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2107.04911 oa: '1' place: Cham publication: The Semantic Web publication_identifier: isbn: - '9783031069802' - '9783031069819' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer International Publishing related_material: link: - relation: confirmation url: https://link.springer.com/chapter/10.1007/978-3-031-06981-9_14 status: public title: Learning Concept Lengths Accelerates Concept Learning in ALC type: book_chapter user_id: '11871' year: '2022' ... --- _id: '29290' 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." author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Lukas full_name: Blübaum, Lukas last_name: Blübaum - first_name: Nick full_name: Düsterhus, Nick last_name: Düsterhus - first_name: Till full_name: Werner, Till last_name: Werner - first_name: Varun Nandkumar full_name: Golani, Varun Nandkumar last_name: Golani - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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.' 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} }' 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.' ieee: 'S. Heindorf et al., “EvoLearner: Learning Description Logics with Evolutionary Algorithms,” in WWW, 2022, pp. 818–828.' mla: 'Heindorf, Stefan, et al. “EvoLearner: Learning Description Logics with Evolutionary Algorithms.” WWW, ACM, 2022, pp. 818–28.' 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.' date_created: 2022-01-12T10:22:53Z date_updated: 2022-10-16T08:49:22Z department: - _id: '574' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2111.04879 oa: '1' page: 818-828 publication: WWW publisher: ACM status: public title: 'EvoLearner: Learning Description Logics with Evolutionary Algorithms' type: conference user_id: '11871' year: '2022' ... --- _id: '34674' 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.' alternative_title: - Increasing Perceived Control and Understanding author: - first_name: Leonie Nora full_name: Sieger, Leonie Nora id: '93402' last_name: Sieger - first_name: Julia full_name: Hermann, Julia last_name: Hermann - first_name: Astrid full_name: Schomäcker, Astrid last_name: Schomäcker - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Christian full_name: Meske, Christian last_name: Meske - first_name: Celine-Chiara full_name: Hey, Celine-Chiara last_name: Hey - first_name: Ayşegül full_name: Doğangün, Ayşegül last_name: Doğangün 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' 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} }' 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. 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.' 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.' conference: end_date: 2022-12-08 location: Christchurch, New Zealand name: 'HAI ''22: International Conference on Human-Agent Interaction' start_date: 2022-12-05 date_created: 2022-12-21T09:48:43Z date_updated: 2023-02-09T14:48:51Z department: - _id: '574' - _id: '760' doi: 10.1145/3527188.3561914 keyword: - human-agent interaction - smart homes - supervised learning - participation language: - iso: eng main_file_link: - url: https://papers.dice-research.org/2022/HAI_SmartHome/User_Involvement_in_Training_Smart_Home_Agents_public.pdf project: - _id: '121' name: 'TRR 318 - B1: TRR 318 - Subproject B1' publication: International Conference on Human-Agent Interaction publication_status: published publisher: ACM quality_controlled: '1' status: public title: User Involvement in Training Smart Home Agents type: conference user_id: '14931' year: '2022' ... --- _id: '33738' author: - first_name: Hamada Mohamed Abdelsamee full_name: Zahera, Hamada Mohamed Abdelsamee id: '72768' last_name: Zahera orcid: 0000-0003-0215-1278 - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Stefan full_name: Balke, Stefan last_name: Balke - first_name: Jonas full_name: Haupt, Jonas last_name: Haupt - first_name: Martin full_name: Voigt, Martin last_name: Voigt - first_name: Carolin full_name: Walter, Carolin last_name: Walter - first_name: Fabian full_name: Witter, Fabian last_name: Witter - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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' 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} }' 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.' 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.' 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.' date_created: 2022-10-15T19:25:42Z date_updated: 2023-06-23T09:20:20Z department: - _id: '574' doi: 10.1007/978-3-031-11609-4_9 language: - iso: eng main_file_link: - open_access: '1' url: https://2022.eswc-conferences.org/wp-content/uploads/2022/05/pd_Zahera_et_al_paper_230.pdf oa: '1' place: Cham publication: 'The Semantic Web: ESWC 2022 Satellite Events' publication_identifier: isbn: - '9783031116087' - '9783031116094' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer International Publishing status: public title: 'Tab2Onto: Unsupervised Semantification with Knowledge Graph Embeddings' type: book_chapter user_id: '72768' year: '2022' ... --- _id: '33739' abstract: - lang: eng 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. author: - first_name: Alexander full_name: Bondarenko, Alexander last_name: Bondarenko - first_name: Magdalena full_name: Wolska, Magdalena last_name: Wolska - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Lukas full_name: Blübaum, Lukas last_name: Blübaum - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo - first_name: Benno full_name: Stein, Benno last_name: Stein - first_name: Pavel full_name: Braslavski, Pavel last_name: Braslavski - first_name: Matthias full_name: Hagen, Matthias last_name: Hagen - first_name: Martin full_name: Potthast, Martin last_name: Potthast citation: 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.' 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} }' 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.' 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.' 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.' 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.' date_created: 2022-10-15T19:33:10Z date_updated: 2023-07-02T18:14:01Z department: - _id: '574' - _id: '760' language: - iso: eng main_file_link: - open_access: '1' url: https://aclanthology.org/2022.coling-1.291.pdf oa: '1' page: 3296–3308 place: Gyeongju, Republic of Korea project: - _id: '52' name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing' publication: Proceedings of the 29th International Conference on Computational Linguistics publisher: International Committee on Computational Linguistics status: public title: 'CausalQA: A Benchmark for Causal Question Answering' type: conference user_id: '11871' year: '2022' ... --- _id: '29851' author: - first_name: 'Svetlana ' full_name: 'Pestryakova, Svetlana ' last_name: Pestryakova - first_name: Daniel full_name: Vollmers, Daniel last_name: Vollmers - first_name: Mohamed full_name: Sherif, Mohamed id: '67234' last_name: Sherif orcid: https://orcid.org/0000-0002-9927-2203 - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: 'Muhammad ' full_name: 'Saleem, Muhammad ' last_name: Saleem - first_name: Diego full_name: Moussallem, Diego id: '71635' last_name: Moussallem - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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} }' 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.' ieee: 'S. Pestryakova et al., “CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications,” Scientific Data, 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). date_created: 2022-02-15T16:59:29Z date_updated: 2023-08-16T10:01:49Z department: - _id: '574' language: - iso: eng main_file_link: - open_access: '1' url: https://papers.dice-research.org/2022/NSDJ_CovidPubGraph/public.pdf oa: '1' publication: Scientific Data status: public title: 'CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications' type: journal_article user_id: '67234' year: '2022' ... --- _id: '33957' 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. author: - first_name: Sahar full_name: Deppe, Sahar last_name: Deppe - first_name: Lukas full_name: Brandt, Lukas last_name: Brandt - first_name: Marc full_name: Brünninghaus, Marc last_name: Brünninghaus - first_name: Jörg full_name: Papenkordt, Jörg id: '44648' last_name: Papenkordt - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Gudrun full_name: Tschirner-Vinke, Gudrun last_name: Tschirner-Vinke citation: 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 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)} }' 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.' mla: Deppe, Sahar, et al. 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). conference: end_date: 2022-09-09 location: Stuttgart name: ETFA start_date: 2022-09-06 date_created: 2022-10-28T11:43:49Z date_updated: 2023-11-23T08:07:51Z department: - _id: '178' - _id: '574' - _id: '184' doi: 10.1109/ETFA52439.2022.9921520 keyword: - Assistance system - Knowledge graph - Information retrieval - Neural networks - AR language: - iso: eng project: - _id: '409' grant_number: 02L19C115 name: 'KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands in OstWestfalenLippe' related_material: link: - relation: confirmation url: https://ieeexplore.ieee.org/document/9921520 series_title: 2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA) status: public title: AI-Based Assistance System for Manufacturing type: conference user_id: '44648' year: '2022' ... --- _id: '29291' author: - first_name: Hamada Mohamed Abdelsamee full_name: Zahera, Hamada Mohamed Abdelsamee id: '72768' last_name: Zahera - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille last_name: Ngonga Ngomo citation: 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' 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' 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} }' 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.' 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.' 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.' short: 'H.M.A. Zahera, S. Heindorf, A.-C. Ngonga Ngomo, in: Proceedings of the 11th on Knowledge Capture Conference, ACM, 2021.' date_created: 2022-01-12T10:27:02Z date_updated: 2022-10-15T19:40:49Z department: - _id: '574' doi: 10.1145/3460210.3493563 language: - iso: eng main_file_link: - open_access: '1' url: https://papers.dice-research.org/2021/KCAP2021_ASSET/public.pdf oa: '1' publication: Proceedings of the 11th on Knowledge Capture Conference publication_status: published publisher: ACM status: public title: 'ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs' type: conference user_id: '11871' year: '2021' ... --- _id: '29292' author: - first_name: Robert full_name: Feldhans, Robert last_name: Feldhans - first_name: Adrian full_name: Wilke, Adrian id: '9101' last_name: Wilke orcid: 0000-0002-6575-807X - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Mohammad Hossein full_name: Shaker, Mohammad Hossein last_name: Shaker - first_name: Barbara full_name: Hammer, Barbara last_name: Hammer - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: 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' 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 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} }' 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.' 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. 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.' date_created: 2022-01-12T10:27:23Z date_updated: 2022-10-15T19:54:20Z department: - _id: '574' doi: 10.1007/978-3-030-91608-4_11 language: - iso: eng main_file_link: - open_access: '1' url: https://papers.dice-research.org/2021/IDEAL2021_DriftDetectionEmbeddings/Drift-Detection-in-Text-Data-with-Document-Embeddings-public.pdf oa: '1' place: Cham publication: Intelligent Data Engineering and Automated Learning – IDEAL 2021 publication_identifier: isbn: - '9783030916077' - '9783030916084' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer International Publishing related_material: link: - relation: confirmation url: https://link.springer.com/chapter/10.1007/978-3-030-91608-4_11 status: public title: Drift Detection in Text Data with Document Embeddings type: book_chapter user_id: '11871' year: '2021' ... --- _id: '29287' abstract: - lang: eng 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." author: - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Diego full_name: Moussallem, Diego id: '71635' last_name: Moussallem - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: 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.' 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. 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} }' 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. ieee: C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional Hypercomplex Embeddings for Link Prediction,” 2021. mla: Demir, Caglar, et al. “Convolutional Hypercomplex Embeddings for Link Prediction.” The 13th Asian Conference on Machine Learning, ACML 2021, 2021. short: 'C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021.' date_created: 2022-01-12T10:21:10Z date_updated: 2022-10-17T15:06:40Z department: - _id: '574' external_id: arxiv: - '2106.15230' language: - iso: eng main_file_link: - open_access: '1' url: https://papers.dice-research.org/2021/ACML2021_HyperConv/public.pdf oa: '1' publication: The 13th Asian Conference on Machine Learning, ACML 2021 status: public title: Convolutional Hypercomplex Embeddings for Link Prediction type: conference user_id: '11871' year: '2021' ... --- _id: '29294' author: - first_name: Tobias full_name: Nickchen, Tobias id: '27340' last_name: Nickchen orcid: 0000-0001-8958-9330 - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels citation: 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' 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 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} }' 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.' 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. short: 'T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021.' date_created: 2022-01-12T10:31:42Z date_updated: 2022-10-17T15:07:38Z department: - _id: '66' - _id: '574' doi: 10.1109/wacv48630.2021.00204 language: - iso: eng main_file_link: - open_access: '1' url: https://openaccess.thecvf.com/content/WACV2021/papers/Nickchen_Generating_Physically_Sound_Training_Data_for_Image_Recognition_of_Additively_WACV_2021_paper.pdf oa: '1' project: - _id: '52' name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing' publication: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) publication_status: published publisher: IEEE status: public title: Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts type: conference user_id: '11871' year: '2021' ... --- _id: '33733' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 citation: ama: Heindorf S. Automatically generating instructions from tutorials for search and user navigation. Published online 2021. apa: Heindorf, S. (2021). Automatically generating instructions from tutorials for search and user navigation. bibtex: '@article{Heindorf_2021, title={Automatically generating instructions from tutorials for search and user navigation}, author={Heindorf, Stefan}, year={2021} }' chicago: Heindorf, Stefan. “Automatically Generating Instructions from Tutorials for Search and User Navigation,” 2021. ieee: S. Heindorf, “Automatically generating instructions from tutorials for search and user navigation.” 2021. mla: Heindorf, Stefan. Automatically Generating Instructions from Tutorials for Search and User Navigation. 2021. short: S. Heindorf, (2021). date_created: 2022-10-15T19:19:10Z date_updated: 2022-10-17T15:21:49Z ipc: 'US15/885,363 ' ipn: '10936684' main_file_link: - open_access: '1' url: https://patentimages.storage.googleapis.com/f6/21/79/657191c3dfe93b/US10936684.pdf oa: '1' publication_date: 2021-03-02 status: public title: Automatically generating instructions from tutorials for search and user navigation type: patent user_id: '11871' year: '2021' ... --- _id: '20141' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Yan full_name: Scholten, Yan last_name: Scholten - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo - first_name: Martin full_name: Potthast, Martin last_name: Potthast citation: 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. Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020), 3023–3030. https://doi.org/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} }' chicago: 'Heindorf, Stefan, Yan Scholten, Henning Wachsmuth, Axel-Cyrille Ngonga Ngomo, and Martin 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), 3023–30, 2020. https://doi.org/10.1145/3340531.3412763.' ieee: 'S. 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.' 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.' 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.' date_created: 2020-10-20T13:11:14Z date_updated: 2022-10-15T19:57:01Z department: - _id: '574' doi: 10.1145/3340531.3412763 language: - iso: eng main_file_link: - open_access: '1' url: https://papers.dice-research.org/2020/CIKM-20/heindorf_2020a_public.pdf oa: '1' page: 3023-3030 project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2020) status: public title: 'CauseNet: Towards a Causality Graph Extracted from the Web' type: conference user_id: '11871' year: '2020' ... --- _id: '7668' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Yan full_name: Scholten, Yan last_name: Scholten - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels - first_name: Martin full_name: Potthast, Martin last_name: Potthast citation: ama: 'Heindorf S, Scholten Y, Engels G, Potthast M. Debiasing Vandalism Detection Models at Wikidata. In: WWW. ACM; 2019:670-680. doi:10.1145/3308558.3313507' apa: 'Heindorf, S., Scholten, Y., Engels, G., & Potthast, M. (2019). Debiasing Vandalism Detection Models at Wikidata. In WWW (pp. 670–680). San Francisco, USA: ACM. https://doi.org/10.1145/3308558.3313507' bibtex: '@inproceedings{Heindorf_Scholten_Engels_Potthast_2019, title={Debiasing Vandalism Detection Models at Wikidata}, DOI={10.1145/3308558.3313507}, booktitle={WWW}, publisher={ACM}, author={Heindorf, Stefan and Scholten, Yan and Engels, Gregor and Potthast, Martin}, year={2019}, pages={670–680} }' chicago: Heindorf, Stefan, Yan Scholten, Gregor Engels, and Martin Potthast. “Debiasing Vandalism Detection Models at Wikidata.” In WWW, 670–80. ACM, 2019. https://doi.org/10.1145/3308558.3313507. ieee: S. Heindorf, Y. Scholten, G. Engels, and M. Potthast, “Debiasing Vandalism Detection Models at Wikidata,” in WWW, San Francisco, USA, 2019, pp. 670–680. mla: Heindorf, Stefan, et al. “Debiasing Vandalism Detection Models at Wikidata.” WWW, ACM, 2019, pp. 670–80, doi:10.1145/3308558.3313507. short: 'S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: WWW, ACM, 2019, pp. 670–680.' conference: end_date: 2015-05-17 location: San Francisco, USA name: 2019 World Wide Web Conference (WWW '19) start_date: 2019-05-13 date_created: 2019-02-13T14:10:36Z date_updated: 2022-01-06T07:03:43Z ddc: - '000' department: - _id: '66' doi: 10.1145/3308558.3313507 file: - access_level: closed content_type: application/pdf creator: heindorf date_created: 2019-04-27T06:09:45Z date_updated: 2019-04-27T06:09:45Z file_id: '9518' file_name: heindorf2019_WWW.pdf file_size: 1302648 relation: main_file success: 1 file_date_updated: 2019-04-27T06:09:45Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2019_WWW.pdf oa: '1' page: 670-680 project: - _id: '17' name: SFB 901 - Subproject C5 - _id: '4' name: SFB 901 - Project Area C - _id: '1' name: SFB 901 publication: WWW publication_identifier: unknown: - 978-1-4503-6674-8/19/05 publisher: ACM status: public title: Debiasing Vandalism Detection Models at Wikidata type: conference user_id: '11871' year: '2019' ... --- _id: '15333' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 citation: 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} }' chicago: Heindorf, Stefan. Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn, 2019. ieee: S. Heindorf, Vandalism Detection in Crowdsourced Knowledge Bases. Universität Paderborn, 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. date_created: 2019-12-17T06:15:38Z date_updated: 2022-01-06T06:52:20Z ddc: - '040' department: - _id: '66' file: - access_level: closed content_type: application/pdf creator: florida date_created: 2020-01-16T12:09:52Z date_updated: 2020-01-16T12:09:52Z file_id: '15603' file_name: Dissertation_Stefan_Heindorf.pdf file_size: 1740910 relation: main_file success: 1 file_date_updated: 2020-01-16T12:09:52Z has_accepted_license: '1' language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '4' name: SFB 901 - Project Area C - _id: '17' name: SFB 901 - Subproject C5 publisher: Universität Paderborn status: public supervisor: - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels title: Vandalism Detection in Crowdsourced Knowledge Bases type: dissertation user_id: '477' year: '2019' ... --- _id: '14568' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Yan full_name: Scholten, Yan last_name: Scholten - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels - first_name: Martin full_name: Potthast, Martin last_name: Potthast citation: 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 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} }' 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. ieee: S. Heindorf, Y. Scholten, G. Engels, and M. Potthast, “Debiasing Vandalism Detection Models at Wikidata (Extended Abstract),” in INFORMATIK, 2019, pp. 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. short: 'S. Heindorf, Y. Scholten, G. Engels, M. Potthast, in: INFORMATIK, 2019, pp. 289–290.' date_created: 2019-11-05T15:48:52Z date_updated: 2022-01-06T06:52:03Z department: - _id: '66' doi: 10.18420/inf2019_48 language: - iso: eng main_file_link: - open_access: '1' url: https://dl.gi.de/bitstream/handle/20.500.12116/24997/paper3_25.pdf oa: '1' page: 289-290 publication: INFORMATIK status: public title: Debiasing Vandalism Detection Models at Wikidata (Extended Abstract) type: conference user_id: '11871' year: '2019' ... --- _id: '5831' 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. author: - first_name: Dennis full_name: Wolters, Dennis id: '11308' last_name: Wolters - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Jonas full_name: Kirchhoff, Jonas id: '39928' last_name: Kirchhoff - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels citation: 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' 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' 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} }' 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.' 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.' 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.' 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.' date_created: 2018-11-26T11:52:59Z date_updated: 2022-10-15T20:00:17Z department: - _id: '66' doi: 10.1007/978-3-319-91764-1_36 editor: - first_name: Lars full_name: Braubach, Lars last_name: Braubach - first_name: Juan M. full_name: Murillo, Juan M. last_name: Murillo - first_name: Nima full_name: Kaviani, Nima last_name: Kaviani - first_name: Manuel full_name: Lama, Manuel last_name: Lama - first_name: Loli full_name: Burgueño, Loli last_name: Burgueño - first_name: Naouel full_name: Moha, Naouel last_name: Moha - first_name: Marc full_name: Oriol, Marc last_name: Oriol language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/wolters2017_ICSOC_demo.pdf oa: '1' page: 388-392 place: Cham publication: Service-Oriented Computing -- ICSOC 2017 Workshops publication_identifier: isbn: - 978-3-319-91764-1 publisher: Springer International Publishing status: public title: 'Semantic Data Mediator: Linking Services to Websites' type: conference user_id: '11871' year: '2018' ... --- _id: '6721' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Martin full_name: Potthast, Martin last_name: Potthast - first_name: Hannah full_name: Bast, Hannah last_name: Bast - first_name: Björn full_name: Buchhold, Björn last_name: Buchhold - first_name: Elmar full_name: Haussmann, Elmar last_name: Haussmann citation: 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.' 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.' 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.' mla: 'Heindorf, Stefan, et al. “WSDM Cup 2017: Vandalism Detection and Triple Scoring.” WSDM, ACM, 2017, pp. 827–28.' short: 'S. Heindorf, M. Potthast, H. Bast, B. Buchhold, E. Haussmann, in: WSDM, ACM, 2017, pp. 827–828.' date_created: 2019-01-15T08:54:23Z date_updated: 2022-01-06T07:03:17Z department: - _id: '66' language: - iso: eng main_file_link: - open_access: '1' url: https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/heindorf2017_WSDM.pdf oa: '1' page: 827-828 publication: WSDM publisher: ACM status: public title: 'WSDM Cup 2017: Vandalism Detection and Triple Scoring' type: conference user_id: '11871' year: '2017' ... --- _id: '5829' abstract: - lang: eng 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. author: - first_name: Dennis full_name: Wolters, Dennis id: '11308' last_name: Wolters - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Jonas full_name: Kirchhoff, Jonas id: '39928' last_name: Kirchhoff - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels 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 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} }' 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. 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.' 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. 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.' date_created: 2018-11-26T11:49:31Z date_updated: 2022-10-15T20:01:55Z department: - _id: '66' doi: 10.1109/icws.2017.80 editor: - first_name: Ilkay full_name: Altintas, Ilkay last_name: Altintas - first_name: Shiping full_name: Chen, Shiping last_name: Chen keyword: - Services - Websites - Semantic Data - schema.org - Data Conversion - Interface Adaptation - Mediation language: - iso: eng main_file_link: - open_access: '1' url: https://cs.uni-paderborn.de/fileadmin/informatik/fg/dbis/Publikationen/2017/wolters2017_ICWS.pdf oa: '1' publication: 2017 IEEE International Conference on Web Services (ICWS) publication_identifier: isbn: - '9781538607527' publication_status: published publisher: IEEE status: public title: Linking Services to Websites by Leveraging Semantic Data type: conference user_id: '11871' year: '2017' ... --- _id: '6722' abstract: - lang: eng 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." author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Martin full_name: Potthast, Martin last_name: Potthast - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels - first_name: Benno full_name: Stein, Benno last_name: Stein citation: 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.' 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. 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} }' 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. ieee: S. Heindorf, M. Potthast, G. Engels, and B. Stein, “Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017,” 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.' date_created: 2019-01-15T08:57:40Z date_updated: 2022-10-17T11:36:12Z department: - _id: '66' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1712.05956 oa: '1' publication: WSDM Cup 2017 Notebook Papers status: public title: Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017 type: conference user_id: '11871' year: '2017' ... --- _id: '33732' abstract: - lang: eng 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." author: - first_name: Martin full_name: Potthast, Martin last_name: Potthast - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Hannah full_name: Bast, Hannah last_name: Bast citation: 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.' 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} }' chicago: 'Potthast, Martin, Stefan Heindorf, and Hannah Bast. “Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring.” ArXiv:1712.09528, 2017.' ieee: 'M. Potthast, S. Heindorf, and H. Bast, “Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring,” arXiv:1712.09528. 2017.' mla: 'Potthast, Martin, et al. “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). date_created: 2022-10-15T19:14:01Z date_updated: 2022-10-17T11:21:00Z department: - _id: '66' external_id: arxiv: - '1712.09528' language: - iso: eng publication: arXiv:1712.09528 status: public title: 'Proceedings of the WSDM Cup 2017: Vandalism Detection and Triple Scoring' type: preprint user_id: '11871' year: '2017' ... --- _id: '137' 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). author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Matthias full_name: Potthast, Matthias last_name: Potthast - first_name: Benno full_name: Stein, Benno last_name: Stein - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels citation: ama: 'Heindorf S, Potthast M, Stein B, Engels G. Vandalism Detection in Wikidata. In: Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016). ; 2016:327--336. doi:10.1145/2983323.2983740' apa: Heindorf, S., Potthast, M., Stein, B., & Engels, G. (2016). Vandalism Detection in Wikidata. Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 327--336. https://doi.org/10.1145/2983323.2983740 bibtex: '@inproceedings{Heindorf_Potthast_Stein_Engels_2016, title={Vandalism Detection in Wikidata}, DOI={10.1145/2983323.2983740}, booktitle={Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016)}, author={Heindorf, Stefan and Potthast, Matthias and Stein, Benno and Engels, Gregor}, year={2016}, pages={327--336} }' chicago: Heindorf, Stefan, Matthias Potthast, Benno Stein, and Gregor Engels. “Vandalism Detection in Wikidata.” In Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 327--336, 2016. https://doi.org/10.1145/2983323.2983740. ieee: 'S. Heindorf, M. Potthast, B. Stein, and G. Engels, “Vandalism Detection in Wikidata,” in Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 2016, pp. 327--336, doi: 10.1145/2983323.2983740.' mla: Heindorf, Stefan, et al. “Vandalism Detection in Wikidata.” Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 2016, pp. 327--336, doi:10.1145/2983323.2983740. short: 'S. Heindorf, M. Potthast, B. Stein, G. Engels, in: Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016), 2016, pp. 327--336.' date_created: 2017-10-17T12:41:18Z date_updated: 2022-10-17T11:31:41Z ddc: - '040' department: - _id: '66' doi: 10.1145/2983323.2983740 file: - access_level: closed content_type: application/pdf creator: florida date_created: 2018-03-21T13:01:43Z date_updated: 2018-03-21T13:01:43Z file_id: '1561' file_name: 137-p327-heindorf.pdf file_size: 1842753 relation: main_file success: 1 file_date_updated: 2018-03-21T13:01:43Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2016_CIKM.pdf oa: '1' page: 327--336 project: - _id: '1' name: SFB 901 - _id: '17' name: SFB 901 - Subprojekt C5 - _id: '4' name: SFB 901 - Project Area C publication: Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016) status: public title: Vandalism Detection in Wikidata type: conference user_id: '11871' year: '2016' ... --- _id: '6719' author: - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Martin full_name: Potthast, Martin last_name: Potthast - first_name: Benno full_name: Stein, Benno last_name: Stein - first_name: Gregor full_name: Engels, Gregor id: '107' last_name: Engels citation: ama: 'Heindorf S, Potthast M, Stein B, Engels G. Towards Vandalism Detection in Knowledge Bases. In: SIGIR. ACM; 2015:831-834. doi:10.1145/2766462.2767804' apa: Heindorf, S., Potthast, M., Stein, B., & Engels, G. (2015). Towards Vandalism Detection in Knowledge Bases. SIGIR, 831–834. https://doi.org/10.1145/2766462.2767804 bibtex: '@inproceedings{Heindorf_Potthast_Stein_Engels_2015, title={Towards Vandalism Detection in Knowledge Bases}, DOI={10.1145/2766462.2767804}, booktitle={SIGIR}, publisher={ACM}, author={Heindorf, Stefan and Potthast, Martin and Stein, Benno and Engels, Gregor}, year={2015}, pages={831–834} }' chicago: Heindorf, Stefan, Martin Potthast, Benno Stein, and Gregor Engels. “Towards Vandalism Detection in Knowledge Bases.” In SIGIR, 831–34. ACM, 2015. https://doi.org/10.1145/2766462.2767804. ieee: 'S. Heindorf, M. Potthast, B. Stein, and G. Engels, “Towards Vandalism Detection in Knowledge Bases,” in SIGIR, 2015, pp. 831–834, doi: 10.1145/2766462.2767804.' mla: Heindorf, Stefan, et al. “Towards Vandalism Detection in Knowledge Bases.” SIGIR, ACM, 2015, pp. 831–34, doi:10.1145/2766462.2767804. short: 'S. Heindorf, M. Potthast, B. Stein, G. Engels, in: SIGIR, ACM, 2015, pp. 831–834.' date_created: 2019-01-15T08:45:08Z date_updated: 2022-10-17T15:07:08Z ddc: - '000' department: - _id: '66' doi: 10.1145/2766462.2767804 file: - access_level: closed content_type: application/pdf creator: heindorf date_created: 2019-04-27T06:06:08Z date_updated: 2019-04-27T06:06:08Z file_id: '9517' file_name: heindorf2015_SIGIR.pdf file_size: 322456 relation: main_file success: 1 file_date_updated: 2019-04-27T06:06:08Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/fg-engels/publications_pdfs/Konferenzbeitraege/heindorf2015_SIGIR.pdf oa: '1' page: 831-834 publication: SIGIR publication_identifier: isbn: - '9781450336215' publication_status: published publisher: ACM status: public title: Towards Vandalism Detection in Knowledge Bases type: conference user_id: '11871' year: '2015' ... --- _id: '6720' author: - first_name: Stefan full_name: Böttcher, Stefan id: '624' last_name: Böttcher - first_name: Rita full_name: Hartel, Rita id: '14961' last_name: Hartel - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 citation: ama: 'Böttcher S, Hartel R, Heindorf S. Optimized XPath evaluation for Schema-compressed XML data. In: ADC. Vol 124. {CRPIT}. Australian Computer Society; 2012:137-144.' apa: Böttcher, S., Hartel, R., & Heindorf, S. (2012). Optimized XPath evaluation for Schema-compressed XML data. In ADC (Vol. 124, pp. 137–144). Australian Computer Society. bibtex: '@inproceedings{Böttcher_Hartel_Heindorf_2012, series={{CRPIT}}, title={Optimized XPath evaluation for Schema-compressed XML data}, volume={124}, booktitle={ADC}, publisher={Australian Computer Society}, author={Böttcher, Stefan and Hartel, Rita and Heindorf, Stefan}, year={2012}, pages={137–144}, collection={{CRPIT}} }' chicago: Böttcher, Stefan, Rita Hartel, and Stefan Heindorf. “Optimized XPath Evaluation for Schema-Compressed XML Data.” In ADC, 124:137–44. {CRPIT}. Australian Computer Society, 2012. ieee: S. Böttcher, R. Hartel, and S. Heindorf, “Optimized XPath evaluation for Schema-compressed XML data,” in ADC, 2012, vol. 124, pp. 137–144. mla: Böttcher, Stefan, et al. “Optimized XPath Evaluation for Schema-Compressed XML Data.” ADC, vol. 124, Australian Computer Society, 2012, pp. 137–44. short: 'S. Böttcher, R. Hartel, S. Heindorf, in: ADC, Australian Computer Society, 2012, pp. 137–144.' date_created: 2019-01-15T08:47:09Z date_updated: 2022-01-06T07:03:17Z department: - _id: '66' intvolume: ' 124' language: - iso: eng page: 137-144 publication: ADC publisher: Australian Computer Society series_title: '{CRPIT}' status: public title: Optimized XPath evaluation for Schema-compressed XML data type: conference user_id: '11871' volume: 124 year: '2012' ...