[{"type":"book_chapter","status":"public","user_id":"114533","department":[{"_id":"34"},{"_id":"574"}],"project":[{"_id":"285","name":"SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen"}],"_id":"62701","publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783032060655","9783032060662"]},"citation":{"ieee":"C. Demir, M. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based OWL Class Expression Learner over Large Graphs,” in <i>Lecture Notes in Computer Science</i>, Cham: Springer Nature Switzerland, 2025.","chicago":"Demir, Caglar, Moshood Yekini, Michael Röder, Yasir Mahmood, and Axel-Cyrille Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large Graphs.” In <i>Lecture Notes in Computer Science</i>. Cham: Springer Nature Switzerland, 2025. <a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">https://doi.org/10.1007/978-3-032-06066-2_29</a>.","ama":"Demir C, Yekini M, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class Expression Learner over Large Graphs. In: <i>Lecture Notes in Computer Science</i>. Springer Nature Switzerland; 2025. doi:<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>","mla":"Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.” <i>Lecture Notes in Computer Science</i>, Springer Nature Switzerland, 2025, doi:<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>.","bibtex":"@inbook{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham}, title={Tree-Based OWL Class Expression Learner over Large Graphs}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">10.1007/978-3-032-06066-2_29</a>}, booktitle={Lecture Notes in Computer Science}, publisher={Springer Nature Switzerland}, author={Demir, Caglar and Yekini, Moshood and Röder, Michael and Mahmood, Yasir and Ngonga Ngomo, Axel-Cyrille}, year={2025} }","short":"C. Demir, M. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.","apa":"Demir, C., Yekini, M., Röder, M., Mahmood, Y., &#38; Ngonga Ngomo, A.-C. (2025). Tree-Based OWL Class Expression Learner over Large Graphs. In <i>Lecture Notes in Computer Science</i>. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML PKDD, Porto, Portugal. Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-032-06066-2_29\">https://doi.org/10.1007/978-3-032-06066-2_29</a>"},"place":"Cham","author":[{"last_name":"Demir","full_name":"Demir, Caglar","first_name":"Caglar"},{"first_name":"Moshood","last_name":"Yekini","full_name":"Yekini, Moshood"},{"last_name":"Röder","full_name":"Röder, Michael","first_name":"Michael"},{"last_name":"Mahmood","full_name":"Mahmood, Yasir","first_name":"Yasir"},{"last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"date_updated":"2025-11-28T14:57:39Z","conference":{"end_date":"2025-09-19","location":"Porto, Portugal","name":"European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML PKDD","start_date":"2025-09-15"},"doi":"10.1007/978-3-032-06066-2_29","publication":"Lecture Notes in Computer Science","abstract":[{"lang":"eng","text":"Learning  continuous  vector  representations  for  knowledge graphs has significantly improved state-of-the-art performances in many challenging tasks. Yet, deep-learning-based models are only post-hoc and locally explainable. In contrast, learning Web Ontology Language (OWL) class  expressions  in  Description  Logics  (DLs)  is  ante-hoc  and  globally explainable. However, state-of-the-art learners have two well-known lim-itations:  scaling  to  large  knowledge  graphs  and  handling  missing  infor-mation.  Here,  we  present  a  decision-tree-based  learner  (tDL)  to  learn Web  Ontology  Languages  (OWLs)  class  expressions  over  large  knowl-edge graphs, while imputing missing triples. Given positive and negative example individuals, tDL  firstly constructs unique OWL expressions in .SHOIN from  concise  bounded  descriptions  of  individuals.  Each  OWL class expression is used as a feature in a binary classification problem to represent input individuals. Thereafter, tDL  fits a CART decision tree to learn Boolean decision rules distinguishing positive examples from nega-tive examples. A final OWL expression in.SHOIN is built by traversing the  built  CART  decision  tree  from  the  root  node  to  leaf  nodes  for  each positive example. By this, tDL  can learn OWL class expressions without exploration, i.e., the number of queries to a knowledge graph is bounded by the number of input individuals. Our empirical results show that tDL outperforms  the  current state-of-the-art  models  across datasets. Impor-tantly, our experiments over a large knowledge graph (DBpedia with 1.1 billion triples) show that tDL  can effectively learn accurate OWL class expressions,  while  the  state-of-the-art  models  fail  to  return  any  results. Finally,  expressions  learned  by  tDL  can  be  seamlessly  translated  into natural language explanations using a pre-trained large language model and a DL verbalizer."}],"language":[{"iso":"eng"}],"keyword":["Decision Tree","OWL Class Expression Learning","Description Logic","Knowledge Graph","Large Language Model","Verbalizer"],"year":"2025","date_created":"2025-11-28T14:09:17Z","publisher":"Springer Nature Switzerland","title":"Tree-Based OWL Class Expression Learner over Large Graphs"},{"type":"conference","abstract":[{"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.","lang":"eng"}],"status":"public","_id":"33957","project":[{"grant_number":"02L19C115","_id":"409","name":"KIAM: KIAM: Kompetenzzentrum KI in der Arbeitswelt des industriellen Mittelstands in OstWestfalenLippe"}],"department":[{"_id":"178"},{"_id":"574"},{"_id":"184"}],"user_id":"44648","series_title":"2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)","keyword":["Assistance system","Knowledge graph","Information retrieval","Neural networks","AR"],"language":[{"iso":"eng"}],"related_material":{"link":[{"relation":"confirmation","url":"https://ieeexplore.ieee.org/document/9921520"}]},"year":"2022","citation":{"apa":"Deppe, S., Brandt, L., Brünninghaus, M., Papenkordt, J., Heindorf, S., &#38; Tschirner-Vinke, G. (2022). <i>AI-Based Assistance System for Manufacturing</i>. ETFA, Stuttgart. <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">https://doi.org/10.1109/ETFA52439.2022.9921520</a>","short":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, G. Tschirner-Vinke, (2022).","mla":"Deppe, Sahar, et al. <i>AI-Based Assistance System for Manufacturing</i>. 2022, doi:<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>.","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={<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>}, author={Deppe, Sahar and Brandt, Lukas and Brünninghaus, Marc and Papenkordt, Jörg and Heindorf, Stefan and Tschirner-Vinke, Gudrun}, year={2022}, collection={2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)} }","ama":"Deppe S, Brandt L, Brünninghaus M, Papenkordt J, Heindorf S, Tschirner-Vinke G. AI-Based Assistance System for Manufacturing. Published online 2022. doi:<a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>","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. <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">https://doi.org/10.1109/ETFA52439.2022.9921520</a>.","ieee":"S. Deppe, L. Brandt, M. Brünninghaus, J. Papenkordt, S. Heindorf, and G. Tschirner-Vinke, “AI-Based Assistance System for Manufacturing.” 2022, doi: <a href=\"https://doi.org/10.1109/ETFA52439.2022.9921520\">10.1109/ETFA52439.2022.9921520</a>."},"date_updated":"2023-11-23T08:07:51Z","date_created":"2022-10-28T11:43:49Z","author":[{"first_name":"Sahar","last_name":"Deppe","full_name":"Deppe, Sahar"},{"first_name":"Lukas","full_name":"Brandt, Lukas","last_name":"Brandt"},{"last_name":"Brünninghaus","full_name":"Brünninghaus, Marc","first_name":"Marc"},{"first_name":"Jörg","id":"44648","full_name":"Papenkordt, Jörg","last_name":"Papenkordt"},{"first_name":"Stefan","last_name":"Heindorf","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","id":"11871"},{"first_name":"Gudrun","full_name":"Tschirner-Vinke, Gudrun","last_name":"Tschirner-Vinke"}],"title":"AI-Based Assistance System for Manufacturing","conference":{"start_date":"2022-09-06","name":"ETFA","location":"Stuttgart","end_date":"2022-09-09"},"doi":"10.1109/ETFA52439.2022.9921520"},{"title":"HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs","date_created":"2022-08-02T11:56:03Z","publisher":"Springer International Publishing","year":"2022","quality_controlled":"1","language":[{"iso":"eng"}],"keyword":["fact checking · ensemble learning · knowledge graph veracit"],"ddc":["000"],"file":[{"file_id":"34853","file_name":"hybrid_fact_check_iswc2022.pdf","access_level":"closed","file_size":296218,"date_created":"2022-12-22T15:45:29Z","creator":"uqudus","date_updated":"2022-12-22T15:45:29Z","relation":"main_file","success":1,"content_type":"application/pdf"}],"abstract":[{"lang":"eng","text":" We consider fact-checking approaches that aim to predict the veracity of assertions in knowledge graphs. Five main categories of fact-checking approaches for knowledge graphs have been proposed in the recent literature, of\r\nwhich each is subject to partially overlapping limitations. In particular, current text-based approaches are limited by manual feature engineering. Path-based and rule-based approaches are limited by their exclusive use of knowledge graphs as background knowledge, and embedding-based approaches suffer from low accuracy scores on current fact-checking tasks. We propose a hybrid approach—dubbed HybridFC—that exploits the diversity of existing categories of fact-checking approaches within an ensemble learning setting to achieve a significantly better prediction performance. In particular, our approach outperforms the state of the art by 0.14 to 0.27 in terms of Area Under the Receiver Operating Characteristic curve on the FactBench dataset. Our code is open-source and can be found at https://github.com/dice-group/HybridFC."}],"publication":"The Semantic Web -- ISWC 2022","conference":{"name":"International Semantic Web Conference (ISWC)","start_date":"2022-10-23","end_date":"2022-10-27","location":"Hanghzou, China"},"doi":"10.1007/978-3-031-19433-7_27","author":[{"id":"83392","full_name":"Qudus, Umair","orcid":"0000-0001-6714-8729","last_name":"Qudus","first_name":"Umair"},{"last_name":"Röder","orcid":"https://orcid.org/0000-0002-8609-8277","full_name":"Röder, Michael","id":"67199","first_name":"Michael"},{"first_name":"Muhammad","full_name":"Saleem, Muhammad","last_name":"Saleem"},{"first_name":"Axel-Cyrille","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo"}],"date_updated":"2025-09-11T09:37:16Z","page":"462--480","citation":{"apa":"Qudus, U., Röder, M., Saleem, M., &#38; Ngonga Ngomo, A.-C. (n.d.). HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs. In U. Sattler, A. Hogan, M. Keet, &#38; V. Presutti (Eds.), <i>The Semantic Web -- ISWC 2022</i> (pp. 462--480). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">https://doi.org/10.1007/978-3-031-19433-7_27</a>","mla":"Qudus, Umair, et al. “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs.” <i>The Semantic Web -- ISWC 2022</i>, edited by Ulrike Sattler et al., Springer International Publishing, pp. 462--480, doi:<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>.","short":"U. Qudus, M. Röder, M. Saleem, A.-C. Ngonga Ngomo, in: U. Sattler, A. Hogan, M. Keet, V. Presutti (Eds.), The Semantic Web -- ISWC 2022, Springer International Publishing, Cham, n.d., pp. 462--480.","bibtex":"@inproceedings{Qudus_Röder_Saleem_Ngonga Ngomo, place={Cham}, title={HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>}, booktitle={The Semantic Web -- ISWC 2022}, publisher={Springer International Publishing}, author={Qudus, Umair and Röder, Michael and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}, editor={Sattler, Ulrike and Hogan, Aidan and Keet, Maria and Presutti, Valentina}, pages={462--480} }","chicago":"Qudus, Umair, Michael Röder, Muhammad Saleem, and Axel-Cyrille Ngonga Ngomo. “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs.” In <i>The Semantic Web -- ISWC 2022</i>, edited by Ulrike Sattler, Aidan Hogan, Maria Keet, and Valentina Presutti, 462--480. Cham: Springer International Publishing, n.d. <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">https://doi.org/10.1007/978-3-031-19433-7_27</a>.","ieee":"U. Qudus, M. Röder, M. Saleem, and A.-C. Ngonga Ngomo, “HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs,” in <i>The Semantic Web -- ISWC 2022</i>, Hanghzou, China, pp. 462--480, doi: <a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>.","ama":"Qudus U, Röder M, Saleem M, Ngonga Ngomo A-C. HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs. In: Sattler U, Hogan A, Keet M, Presutti V, eds. <i>The Semantic Web -- ISWC 2022</i>. Springer International Publishing; :462--480. doi:<a href=\"https://doi.org/10.1007/978-3-031-19433-7_27\">10.1007/978-3-031-19433-7_27</a>"},"place":"Cham","has_accepted_license":"1","publication_identifier":{"isbn":["978-3-031-19433-7"]},"publication_status":"accepted","file_date_updated":"2022-12-22T15:45:29Z","department":[{"_id":"34"}],"user_id":"83392","_id":"32509","project":[{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"}],"status":"public","editor":[{"full_name":"Sattler, Ulrike","last_name":"Sattler","first_name":"Ulrike"},{"last_name":"Hogan","full_name":"Hogan, Aidan","first_name":"Aidan"},{"first_name":"Maria","last_name":"Keet","full_name":"Keet, Maria"},{"first_name":"Valentina","last_name":"Presutti","full_name":"Presutti, Valentina"}],"popular_science":"1","type":"conference"}]