[{"author":[{"id":"87189","last_name":"KOUAGOU","full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean"},{"first_name":"Stefan","orcid":"0000-0002-4525-6865","full_name":"Heindorf, Stefan","last_name":"Heindorf","id":"11871"},{"id":"43817","last_name":"Demir","full_name":"Demir, Caglar","first_name":"Caglar"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"publisher":"Springer International Publishing","keyword":["Neural network","Concept learning","Description logics"],"publication":"The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)","status":"public","date_created":"2022-10-15T19:20:11Z","volume":13870,"abstract":[{"text":"Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis","lang":"eng"}],"user_id":"11871","main_file_link":[{"open_access":"1","url":"https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf"}],"type":"conference","citation":{"mla":"KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:https://doi.org/10.1007/978-3-031-33455-9_13.","bibtex":"@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis}, volume={13870}, DOI={https://doi.org/10.1007/978-3-031-33455-9_13}, booktitle={The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}, publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, editor={Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}, year={2023}, pages={209–226} }","ama":"KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis. In: Pesquita C, Jimenez-Ruiz E, McCusker J, et al., eds. The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023). Vol 13870. Springer International Publishing; 2023:209-226. doi:https://doi.org/10.1007/978-3-031-33455-9_13","apa":"KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, & S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226). Springer International Publishing. https://doi.org/10.1007/978-3-031-33455-9_13","chicago":"KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis.” In The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita, Ernesto Jimenez-Ruiz, Jamie McCusker, Daniel Faria, Mauro Dragoni, Anastasia Dimou, Raphael Troncy, and Sven Hertling, 13870:209–26. Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-33455-9_13.","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.","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."},"year":"2023","page":"209 - 226","_id":"33734","intvolume":" 13870","conference":{"end_date":"2023-06-01","name":"20th Extended Semantic Web Conference","start_date":"2023-05-28","location":"Hersonissos, Crete, Greece"},"department":[{"_id":"574"},{"_id":"760"}],"project":[{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"},{"grant_number":"101070305","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs","_id":"407"},{"_id":"285","grant_number":"NW21-059D","name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems"}],"editor":[{"first_name":"Catia","full_name":"Pesquita, Catia","last_name":"Pesquita"},{"last_name":"Jimenez-Ruiz","first_name":"Ernesto","full_name":"Jimenez-Ruiz, Ernesto"},{"first_name":"Jamie","full_name":"McCusker, Jamie","last_name":"McCusker"},{"last_name":"Faria","full_name":"Faria, Daniel","first_name":"Daniel"},{"last_name":"Dragoni","first_name":"Mauro","full_name":"Dragoni, Mauro"},{"first_name":"Anastasia","full_name":"Dimou, Anastasia","last_name":"Dimou"},{"full_name":"Troncy, Raphael","first_name":"Raphael","last_name":"Troncy"},{"last_name":"Hertling","first_name":"Sven","full_name":"Hertling, Sven"}],"publication_identifier":{"unknown":["978-3-031-33455-9"]},"publication_status":"published","external_id":{"unknown":["https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13"]},"title":"Neural Class Expression Synthesis","language":[{"iso":"eng"}],"date_updated":"2023-07-02T18:10:02Z","oa":"1","doi":"https://doi.org/10.1007/978-3-031-33455-9_13"},{"date_updated":"2023-07-02T18:10:34Z","_id":"37937","language":[{"iso":"eng"}],"type":"preprint","year":"2023","citation":{"apa":"Sieger, L. N., Heindorf, S., Blübaum, L., & Ngonga Ngomo, A.-C. (2023). Counterfactual Explanations for Concepts in ELH. In arXiv:2301.05109.","ama":"Sieger LN, Heindorf S, Blübaum L, Ngonga Ngomo A-C. Counterfactual Explanations for Concepts in ELH. arXiv:230105109. Published online 2023.","chicago":"Sieger, Leonie Nora, Stefan Heindorf, Lukas Blübaum, and Axel-Cyrille Ngonga Ngomo. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023.","bibtex":"@article{Sieger_Heindorf_Blübaum_Ngonga Ngomo_2023, title={Counterfactual Explanations for Concepts in ELH}, journal={arXiv:2301.05109}, author={Sieger, Leonie Nora and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille}, year={2023} }","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).","ieee":"L. N. Sieger, S. Heindorf, L. Blübaum, and A.-C. Ngonga Ngomo, “Counterfactual Explanations for Concepts in ELH,” arXiv:2301.05109. 2023."},"main_file_link":[{"url":"https://arxiv.org/pdf/2301.05109.pdf"}],"user_id":"11871","title":"Counterfactual Explanations for Concepts in ELH","external_id":{"arxiv":["2301.05109"]},"abstract":[{"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.","lang":"eng"}],"status":"public","date_created":"2023-01-22T19:36:01Z","author":[{"first_name":"Leonie Nora","full_name":"Sieger, Leonie Nora","last_name":"Sieger","id":"93402"},{"first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871"},{"last_name":"Blübaum","full_name":"Blübaum, Lukas","first_name":"Lukas"},{"id":"65716","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"department":[{"_id":"574"},{"_id":"760"}],"publication":"arXiv:2301.05109"},{"oa":"1","_id":"45244","date_updated":"2023-06-30T14:20:31Z","year":"2023","citation":{"chicago":"Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023.","apa":"Lienen, J., & Hüllermeier, E. (2023). Mitigating Label Noise through Data Ambiguation. In arXiv:2305.13764.","ama":"Lienen J, Hüllermeier E. Mitigating Label Noise through Data Ambiguation. arXiv:230513764. Published online 2023.","bibtex":"@article{Lienen_Hüllermeier_2023, title={Mitigating Label Noise through Data Ambiguation}, journal={arXiv:2305.13764}, author={Lienen, Julian and Hüllermeier, Eyke}, year={2023} }","mla":"Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023.","short":"J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).","ieee":"J. Lienen and E. Hüllermeier, “Mitigating Label Noise through Data Ambiguation,” arXiv:2305.13764. 2023."},"type":"preprint","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://arxiv.org/pdf/2305.13764.pdf","open_access":"1"}],"title":"Mitigating Label Noise through Data Ambiguation","user_id":"44040","abstract":[{"lang":"eng","text":"Label noise poses an important challenge in machine learning, especially in\r\ndeep learning, in which large models with high expressive power dominate the\r\nfield. Models of that kind are prone to memorizing incorrect labels, thereby\r\nharming generalization performance. Many methods have been proposed to address\r\nthis problem, including robust loss functions and more complex label correction\r\napproaches. Robust loss functions are appealing due to their simplicity, but\r\ntypically lack flexibility, while label correction usually adds substantial\r\ncomplexity to the training setup. In this paper, we suggest to address the\r\nshortcomings of both methodologies by \"ambiguating\" the target information,\r\nadding additional, complementary candidate labels in case the learner is not\r\nsufficiently convinced of the observed training label. More precisely, we\r\nleverage the framework of so-called superset learning to construct set-valued\r\ntargets based on a confidence threshold, which deliver imprecise yet more\r\nreliable beliefs about the ground-truth, effectively helping the learner to\r\nsuppress the memorization effect. In an extensive empirical evaluation, our\r\nmethod demonstrates favorable learning behavior on synthetic and real-world\r\nnoise, confirming the effectiveness in detecting and correcting erroneous\r\ntraining labels."}],"external_id":{"arxiv":["2305.13764"]},"date_created":"2023-05-24T05:28:34Z","status":"public","publication":"arXiv:2305.13764","author":[{"full_name":"Lienen, Julian","first_name":"Julian","last_name":"Lienen"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","last_name":"Hüllermeier"}]},{"doi":"10.3390/molecules28135109","date_updated":"2023-07-03T08:07:55Z","language":[{"iso":"eng"}],"title":"Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy","publication_status":"published","publication_identifier":{"issn":["1420-3049"]},"department":[{"_id":"302"}],"issue":"13","_id":"45828","intvolume":" 28","page":"5109","type":"journal_article","citation":{"mla":"Duderija, Belma, et al. “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy.” Molecules, vol. 28, no. 13, MDPI AG, 2023, p. 5109, doi:10.3390/molecules28135109.","bibtex":"@article{Duderija_González-Orive_Ebbert_Neßlinger_Keller_Grundmeier_2023, title={Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy}, volume={28}, DOI={10.3390/molecules28135109}, number={13}, journal={Molecules}, publisher={MDPI AG}, author={Duderija, Belma and González-Orive, Alejandro and Ebbert, Christoph and Neßlinger, Vanessa and Keller, Adrian and Grundmeier, Guido}, year={2023}, pages={5109} }","apa":"Duderija, B., González-Orive, A., Ebbert, C., Neßlinger, V., Keller, A., & Grundmeier, G. (2023). Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy. Molecules, 28(13), 5109. https://doi.org/10.3390/molecules28135109","ama":"Duderija B, González-Orive A, Ebbert C, Neßlinger V, Keller A, Grundmeier G. Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy. Molecules. 2023;28(13):5109. doi:10.3390/molecules28135109","chicago":"Duderija, Belma, Alejandro González-Orive, Christoph Ebbert, Vanessa Neßlinger, Adrian Keller, and Guido Grundmeier. “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy.” Molecules 28, no. 13 (2023): 5109. https://doi.org/10.3390/molecules28135109.","ieee":"B. Duderija, A. González-Orive, C. Ebbert, V. Neßlinger, A. Keller, and G. Grundmeier, “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy,” Molecules, vol. 28, no. 13, p. 5109, 2023, doi: 10.3390/molecules28135109.","short":"B. Duderija, A. González-Orive, C. Ebbert, V. Neßlinger, A. Keller, G. Grundmeier, Molecules 28 (2023) 5109."},"year":"2023","user_id":"48864","abstract":[{"lang":"eng","text":"This article presents the potential-dependent adsorption of two proteins, bovine serum albumin (BSA) and lysozyme (LYZ), on Ti6Al4V alloy at pH 7.4 and 37 °C. The adsorption process was studied on an electropolished alloy under cathodic and anodic overpotentials, compared to the open circuit potential (OCP). To analyze the adsorption process, various complementary interface analytical techniques were employed, including PM-IRRAS (polarization-modulation infrared reflection-absorption spectroscopy), AFM (atomic force microscopy), XPS (X-ray photoelectron spectroscopy), and E-QCM (electrochemical quartz crystal microbalance) measurements. The polarization experiments were conducted within a potential range where charging of the electric double layer dominates, and Faradaic currents can be disregarded. The findings highlight the significant influence of the interfacial charge distribution on the adsorption of BSA and LYZ onto the alloy surface. Furthermore, electrochemical analysis of the protein layers formed under applied overpotentials demonstrated improved corrosion protection properties. These studies provide valuable insights into protein adsorption on titanium alloys under physiological conditions, characterized by varying potentials of the passive alloy."}],"date_created":"2023-07-03T08:06:28Z","status":"public","volume":28,"publication":"Molecules","keyword":["Chemistry (miscellaneous)","Analytical Chemistry","Organic Chemistry","Physical and Theoretical Chemistry","Molecular Medicine","Drug Discovery","Pharmaceutical Science"],"publisher":"MDPI AG","author":[{"id":"54863","last_name":"Duderija","full_name":"Duderija, Belma","first_name":"Belma"},{"last_name":"González-Orive","first_name":"Alejandro","full_name":"González-Orive, Alejandro"},{"last_name":"Ebbert","id":"7266","first_name":"Christoph","full_name":"Ebbert, Christoph"},{"first_name":"Vanessa","full_name":"Neßlinger, Vanessa","last_name":"Neßlinger"},{"full_name":"Keller, Adrian","orcid":"0000-0001-7139-3110","first_name":"Adrian","id":"48864","last_name":"Keller"},{"last_name":"Grundmeier","id":"194","first_name":"Guido","full_name":"Grundmeier, Guido"}]},{"year":"2023","citation":{"short":"A. Keller, G. Grundmeier, in: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023.","ieee":"A. Keller and G. Grundmeier, “High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces,” in Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023.","ama":"Keller A, Grundmeier G. High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces. In: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier; 2023. doi:10.1016/b978-0-323-85669-0.00123-9","apa":"Keller, A., & Grundmeier, G. (2023). High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces. In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier. https://doi.org/10.1016/b978-0-323-85669-0.00123-9","chicago":"Keller, Adrian, and Guido Grundmeier. “High-Speed AFM Studies of Macromolecular Dynamics at Solid/Liquid Interfaces.” In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier, 2023. https://doi.org/10.1016/b978-0-323-85669-0.00123-9.","mla":"Keller, Adrian, and Guido Grundmeier. “High-Speed AFM Studies of Macromolecular Dynamics at Solid/Liquid Interfaces.” Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023, doi:10.1016/b978-0-323-85669-0.00123-9.","bibtex":"@inbook{Keller_Grundmeier_2023, title={High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces}, DOI={10.1016/b978-0-323-85669-0.00123-9}, booktitle={Reference Module in Chemistry, Molecular Sciences and Chemical Engineering}, publisher={Elsevier}, author={Keller, Adrian and Grundmeier, Guido}, year={2023} }"},"type":"book_chapter","language":[{"iso":"eng"}],"doi":"10.1016/b978-0-323-85669-0.00123-9","_id":"45829","date_updated":"2023-07-03T08:08:44Z","publication_status":"published","publication_identifier":{"isbn":["9780124095472"]},"date_created":"2023-07-03T08:08:29Z","status":"public","department":[{"_id":"302"}],"publication":"Reference Module in Chemistry, Molecular Sciences and Chemical Engineering","author":[{"full_name":"Keller, Adrian","orcid":"0000-0001-7139-3110","first_name":"Adrian","id":"48864","last_name":"Keller"},{"full_name":"Grundmeier, Guido","first_name":"Guido","id":"194","last_name":"Grundmeier"}],"publisher":"Elsevier","title":"High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces","user_id":"48864"},{"type":"book_chapter","citation":{"ieee":"A. Kostan, “Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft,” in Bedeutung und Implikationen epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023.","short":"A. Kostan, in: Bedeutung Und Implikationen Epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023.","mla":"Kostan, Anastassija. “Die Epistemische Gewalt KI-Basierter Gesichtserkennung. Wie Ein Codierter Blick Neue Formen Der Technologisierten Subalternität Erschafft.” Bedeutung Und Implikationen Epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023, doi:10.5771/9783828877368-253.","bibtex":"@inbook{Kostan_2023, title={Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft}, DOI={10.5771/9783828877368-253}, booktitle={Bedeutung und Implikationen epistemischer Ungerechtigkeit}, publisher={Tectum – ein Verlag in der Nomos Verlagsgesellschaft}, author={Kostan, Anastassija}, year={2023} }","chicago":"Kostan, Anastassija. “Die Epistemische Gewalt KI-Basierter Gesichtserkennung. Wie Ein Codierter Blick Neue Formen Der Technologisierten Subalternität Erschafft.” In Bedeutung Und Implikationen Epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023. https://doi.org/10.5771/9783828877368-253.","apa":"Kostan, A. (2023). Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft. In Bedeutung und Implikationen epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft. https://doi.org/10.5771/9783828877368-253","ama":"Kostan A. Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft. In: Bedeutung Und Implikationen Epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft; 2023. doi:10.5771/9783828877368-253"},"year":"2023","doi":"10.5771/9783828877368-253","_id":"45833","date_updated":"2023-07-03T08:38:39Z","status":"public","date_created":"2023-07-03T08:30:29Z","publication_identifier":{"isbn":["9783828877368"]},"publication_status":"published","publisher":"Tectum – ein Verlag in der Nomos Verlagsgesellschaft","author":[{"last_name":"Kostan","full_name":"Kostan, Anastassija","first_name":"Anastassija"}],"publication":"Bedeutung und Implikationen epistemischer Ungerechtigkeit","user_id":"99059","title":"Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft"},{"abstract":[{"lang":"eng","text":"Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods.\r\nImplicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit\r\n(3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified?\r\nThe uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights.\r\nAs a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain."}],"place":"Neubiberg","title":"Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining","related_material":{"link":[{"relation":"supplementary_material","url":"https://athene-forschung.unibw.de/145003"}]},"user_id":"58701","department":[{"_id":"579"},{"_id":"7"}],"publisher":"Universität der Bundeswehr München ","author":[{"full_name":"Kersting, Joschka","first_name":"Joschka","id":"58701","last_name":"Kersting"}],"publication_status":"published","date_created":"2023-05-02T12:54:00Z","project":[{"_id":"1","grant_number":"160364472","name":"SFB 901: SFB 901"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - B1: SFB 901 - Subproject B1","grant_number":"160364472","_id":"9"}],"status":"public","date_updated":"2023-07-03T12:29:50Z","_id":"44323","page":"208","year":"2023","type":"dissertation","citation":{"short":"J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023.","ieee":"J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.","chicago":"Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.","ama":"Kersting J. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München ; 2023.","apa":"Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München .","mla":"Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München , 2023.","bibtex":"@book{Kersting_2023, place={Neubiberg}, title={Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}, publisher={Universität der Bundeswehr München }, author={Kersting, Joschka}, year={2023} }"},"language":[{"iso":"ger"}],"supervisor":[{"last_name":"Geierhos","id":"42496","first_name":"Michaela","full_name":"Geierhos, Michaela","orcid":"0000-0002-8180-5606"}]},{"doi":"10.3390/bs13070523","date_updated":"2023-07-04T11:14:50Z","language":[{"iso":"eng"}],"title":"A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise","publication_status":"published","publication_identifier":{"issn":["2076-328X"]},"article_number":"523","issue":"7","_id":"45857","intvolume":" 13","citation":{"ieee":"K. Thorenz, A. Berwinkel, and M. Weigelt, “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise,” Behavioral Sciences, vol. 13, no. 7, Art. no. 523, 2023, doi: 10.3390/bs13070523.","short":"K. Thorenz, A. Berwinkel, M. Weigelt, Behavioral Sciences 13 (2023).","bibtex":"@article{Thorenz_Berwinkel_Weigelt_2023, title={A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise}, volume={13}, DOI={10.3390/bs13070523}, number={7523}, journal={Behavioral Sciences}, publisher={MDPI AG}, author={Thorenz, Kristin and Berwinkel, Andre and Weigelt, Matthias}, year={2023} }","mla":"Thorenz, Kristin, et al. “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise.” Behavioral Sciences, vol. 13, no. 7, 523, MDPI AG, 2023, doi:10.3390/bs13070523.","chicago":"Thorenz, Kristin, Andre Berwinkel, and Matthias Weigelt. “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise.” Behavioral Sciences 13, no. 7 (2023). https://doi.org/10.3390/bs13070523.","ama":"Thorenz K, Berwinkel A, Weigelt M. A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise. Behavioral Sciences. 2023;13(7). doi:10.3390/bs13070523","apa":"Thorenz, K., Berwinkel, A., & Weigelt, M. (2023). A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise. Behavioral Sciences, 13(7), Article 523. https://doi.org/10.3390/bs13070523"},"type":"journal_article","year":"2023","user_id":"34992","abstract":[{"text":"The aim of the present study is to prove the construct validity of the German versions of the Feeling Scale (FS) and the Felt Arousal Scale (FAS) for a progressive muscle relaxation (PMR) exercise. A total of 228 sport science students conducted the PMR exercise for 45 min and completed the FS, the FAS, and the Self-Assessment Manikin (SAM) in a pre-test–post-test design. A significant decrease in arousal (t(227) = 8.296, p < 0.001) and a significant increase in pleasure (t(227) = 4.748, p < 0.001) were observed. For convergent validity, the correlations between the FS and the subscale SAM-P for the valence dimension (r = 0.67, p < 0.001) and between the FAS and the subscale SAM-A for the arousal dimension (r = 0.31, p < 0.001) were significant. For discriminant validity, the correlations between different constructs (FS and SAM-A, FAS and SAM-P) were not significant, whereas the discriminant analysis between the FS and the FAS revealed a negative significant correlation (r = −0.15, p < 0.001). Together, the pattern of results confirms the use of the German versions of the FS and the FAS to measure the affective response for a PMR exercise.","lang":"eng"}],"volume":13,"status":"public","date_created":"2023-07-04T11:13:16Z","author":[{"first_name":"Kristin","full_name":"Thorenz, Kristin","last_name":"Thorenz","id":"34992"},{"last_name":"Berwinkel","full_name":"Berwinkel, Andre","first_name":"Andre"},{"last_name":"Weigelt","id":"36388","first_name":"Matthias","full_name":"Weigelt, Matthias"}],"publisher":"MDPI AG","publication":"Behavioral Sciences","keyword":["Behavioral Neuroscience","General Psychology","Genetics","Development","Ecology","Evolution","Behavior and Systematics"]},{"title":"A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training)","publication_status":"published","publication_identifier":{"issn":["2152-7180","2152-7199"]},"doi":"10.4236/psych.2023.146058","date_updated":"2023-07-04T11:14:41Z","language":[{"iso":"eng"}],"user_id":"34992","date_created":"2023-07-04T11:12:13Z","status":"public","volume":14,"keyword":["General Earth and Planetary Sciences","General Environmental Science"],"publication":"Psychology","author":[{"first_name":"Kristin","full_name":"Thorenz, Kristin","last_name":"Thorenz","id":"34992"},{"last_name":"Berwinkel","first_name":"Andre","full_name":"Berwinkel, Andre"},{"first_name":"Matthias","full_name":"Weigelt, Matthias","last_name":"Weigelt","id":"36388"}],"publisher":"Scientific Research Publishing, Inc.","issue":"06","_id":"45856","intvolume":" 14","page":"1070-1084","year":"2023","type":"journal_article","citation":{"chicago":"Thorenz, Kristin, Andre Berwinkel, and Matthias Weigelt. “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training).” Psychology 14, no. 06 (2023): 1070–84. https://doi.org/10.4236/psych.2023.146058.","ama":"Thorenz K, Berwinkel A, Weigelt M. A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training). Psychology. 2023;14(06):1070-1084. doi:10.4236/psych.2023.146058","apa":"Thorenz, K., Berwinkel, A., & Weigelt, M. (2023). A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training). Psychology, 14(06), 1070–1084. https://doi.org/10.4236/psych.2023.146058","mla":"Thorenz, Kristin, et al. “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training).” Psychology, vol. 14, no. 06, Scientific Research Publishing, Inc., 2023, pp. 1070–84, doi:10.4236/psych.2023.146058.","bibtex":"@article{Thorenz_Berwinkel_Weigelt_2023, title={A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training)}, volume={14}, DOI={10.4236/psych.2023.146058}, number={06}, journal={Psychology}, publisher={Scientific Research Publishing, Inc.}, author={Thorenz, Kristin and Berwinkel, Andre and Weigelt, Matthias}, year={2023}, pages={1070–1084} }","short":"K. Thorenz, A. Berwinkel, M. Weigelt, Psychology 14 (2023) 1070–1084.","ieee":"K. Thorenz, A. Berwinkel, and M. Weigelt, “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training),” Psychology, vol. 14, no. 06, pp. 1070–1084, 2023, doi: 10.4236/psych.2023.146058."}},{"department":[{"_id":"5"}],"publication":"Der Deutschunterricht","author":[{"id":"23088","last_name":"Topalović","full_name":"Topalović, Elvira","first_name":"Elvira"},{"first_name":"Alisa","full_name":"Blachut, Alisa","last_name":"Blachut","id":"37811"}],"date_created":"2023-07-04T12:29:21Z","status":"public","volume":3,"publication_status":"published","user_id":"37811","title":"Grammatische Modelle. Einführung in das Themenheft","language":[{"iso":"ger"}],"page":"2–4","citation":{"bibtex":"@article{Topalović_Blachut_2023, title={Grammatische Modelle. Einführung in das Themenheft}, volume={3}, journal={Der Deutschunterricht}, author={Topalović, Elvira and Blachut, Alisa}, year={2023}, pages={2–4} }","mla":"Topalović, Elvira, and Alisa Blachut. “Grammatische Modelle. Einführung in das Themenheft.” Der Deutschunterricht, vol. 3, 2023, pp. 2–4.","ama":"Topalović E, Blachut A. Grammatische Modelle. Einführung in das Themenheft. Der Deutschunterricht. 2023;3:2–4.","apa":"Topalović, E., & Blachut, A. (2023). Grammatische Modelle. Einführung in das Themenheft. Der Deutschunterricht, 3, 2–4.","chicago":"Topalović, Elvira, and Alisa Blachut. “Grammatische Modelle. Einführung in das Themenheft.” Der Deutschunterricht 3 (2023): 2–4.","ieee":"E. Topalović and A. Blachut, “Grammatische Modelle. Einführung in das Themenheft,” Der Deutschunterricht, vol. 3, pp. 2–4, 2023.","short":"E. Topalović, A. Blachut, Der Deutschunterricht 3 (2023) 2–4."},"type":"journal_article","year":"2023","_id":"45861","date_updated":"2023-07-04T12:30:14Z","intvolume":" 3"}]