--- _id: '58076' abstract: - lang: eng text: This paper presents the concept of Information Circularity Assistance, which provides decision support in the early stages of product creation for Circular Economy. Engineers in strategic product planning need to proactively predict the quantity, quality, and timing of secondary materials and returned components. For example, products with high recycled content will only be economically sustainable if the material is actually available in the future product life. Our assumption is that Information Circularity Assistance enables decision makers to incorporate insights from extreme data – high-volume, high-velocity, heterogeneous and distributed data from the product life – into product creation through intelligent Digital Twins. Artificial Intelligence can help to derive sustainable actions in favor of circular products by processing extreme data and enriching it with expert knowledge. The research contributes in three key dimensions. First, a comprehensive literature review is conducted. This review covers concepts of intelligence in Scenario-Technique for strategic product planning, Digital Twin-based analysis of extreme data and relevant technologies from Data Science and Artificial Intelligence. In all areas, the state of the art and emerging trends are identified. Secondly, the study identifies information needs along the steps of the Scenario-Technique and information offerings based on Digital Twins. The concept of Information Circularity Assistance results from the coupling of these demands and offerings, extending the Scenario-Technique beyond traditional expert-based methods. Third, we extend existing Digital Twin methods used in circularity and discuss the deployment of Data Science and Artificial Intelligence algorithms within the product creation process. Our approach uses extreme data to provide a strategic advantage in optimizing product life cycle planning, which is illustrated by two sample applications. The aim is to provide Information Circularity Assistance that will support experienced product planners, developers, and decision makers in the future. alternative_title: - Utilizing Artificial Intelligence, Scenario-Technique and Digital Twins to solve challenges of product creation for Circular Economy article_type: original author: - first_name: Iris full_name: Gräßler, Iris id: '47565' last_name: Gräßler orcid: 0000-0001-5765-971X - first_name: Michael full_name: Weyrich, Michael last_name: Weyrich - first_name: Jens full_name: Pottebaum, Jens id: '405' last_name: Pottebaum orcid: http://orcid.org/0000-0001-8778-2989 - first_name: Simon full_name: Kamm, Simon last_name: Kamm citation: ama: Gräßler I, Weyrich M, Pottebaum J, Kamm S. Information Circularity Assistance based on extreme data. at - Automatisierungstechnik. 2025;73(1):3-21. doi:10.1515/auto-2024-0039 apa: Gräßler, I., Weyrich, M., Pottebaum, J., & Kamm, S. (2025). Information Circularity Assistance based on extreme data. At - Automatisierungstechnik, 73(1), 3–21. https://doi.org/10.1515/auto-2024-0039 bibtex: '@article{Gräßler_Weyrich_Pottebaum_Kamm_2025, title={Information Circularity Assistance based on extreme data}, volume={73}, DOI={10.1515/auto-2024-0039}, number={1}, journal={at - Automatisierungstechnik}, publisher={Walter de Gruyter GmbH}, author={Gräßler, Iris and Weyrich, Michael and Pottebaum, Jens and Kamm, Simon}, year={2025}, pages={3–21} }' chicago: 'Gräßler, Iris, Michael Weyrich, Jens Pottebaum, and Simon Kamm. “Information Circularity Assistance Based on Extreme Data.” At - Automatisierungstechnik 73, no. 1 (2025): 3–21. https://doi.org/10.1515/auto-2024-0039.' ieee: 'I. Gräßler, M. Weyrich, J. Pottebaum, and S. Kamm, “Information Circularity Assistance based on extreme data,” at - Automatisierungstechnik, vol. 73, no. 1, pp. 3–21, 2025, doi: 10.1515/auto-2024-0039.' mla: Gräßler, Iris, et al. “Information Circularity Assistance Based on Extreme Data.” At - Automatisierungstechnik, vol. 73, no. 1, Walter de Gruyter GmbH, 2025, pp. 3–21, doi:10.1515/auto-2024-0039. short: I. Gräßler, M. Weyrich, J. Pottebaum, S. Kamm, At - Automatisierungstechnik 73 (2025) 3–21. date_created: 2025-01-07T13:30:45Z date_updated: 2025-02-15T09:41:54Z department: - _id: '152' doi: 10.1515/auto-2024-0039 intvolume: ' 73' issue: '1' keyword: - Scenario-Technique - Artificial Intelligence - Digital Twin - Large Language Models language: - iso: eng main_file_link: - open_access: '1' oa: '1' page: 3-21 publication: at - Automatisierungstechnik publication_identifier: issn: - 0178-2312 - 2196-677X publication_status: published publisher: Walter de Gruyter GmbH quality_controlled: '1' status: public title: Information Circularity Assistance based on extreme data type: journal_article user_id: '405' volume: 73 year: '2025' ... --- _id: '58822' abstract: - lang: eng text: 'In 1921, John Wisdom (1904–1993) became a member of Fitzwilliam House, Cambridge, where he read philosophy and attended lectures by G. E. Moore, C. D. Broad, and J. E. McTaggart. He received his BA in 1924, after which he worked for five years at the National Institute of Industrial Psychology. From 1929 to 1934, Wisdom was a Lecturer in the department of logic and metaphysics at the University of St Andrews and a colleague of G. F. Stout. After the publication of his book Interpretation and Analysis (1931) and five articles on “Logical Constructions” in Mind (1931–3), Wisdom became a Lecturer in Moral Sciences in Cambridge and a Fellow of Trinity College. This gave him the opportunity to gain first-hand knowledge of Wittgenstein’s philosophy. Since nothing by Wittgenstein but Tractatus appeared in print for decades, Wisdom’s publications of these years were—mistakenly—read as portents of the new ideas of Wittgenstein himself. The publication of Wittgenstein’s Philosophical Investigations in 1953 brought with it, among other things, the fall of Wisdom’s popularity. ' author: - first_name: Nikolay full_name: Milkov, Nikolay id: '357' last_name: Milkov citation: ama: 'Milkov N. Wisdom’s Wittgenstein. In: Khani AH, Kemp G, eds. Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 Vol., Volume II. 1st ed. Routledge.' apa: 'Milkov, N. (n.d.). Wisdom’s Wittgenstein. In A. H. Khani & G. Kemp (Eds.), Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 vol., Volume II (1st ed.). Routledge.' bibtex: '@inbook{Milkov, place={London}, edition={1}, title={Wisdom’s Wittgenstein}, booktitle={Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 vol., Volume II}, publisher={Routledge}, author={Milkov, Nikolay}, editor={Khani , Ali Hossein and Kemp , Gary } }' chicago: 'Milkov, Nikolay. “Wisdom’s Wittgenstein.” In Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 Vol., Volume II, edited by Ali Hossein Khani and Gary Kemp , 1st ed. London: Routledge, n.d.' ieee: 'N. Milkov, “Wisdom’s Wittgenstein,” in Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 vol., Volume II, 1st ed., A. H. Khani and G. Kemp , Eds. London: Routledge.' mla: 'Milkov, Nikolay. “Wisdom’s Wittgenstein.” Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 Vol., Volume II, edited by Ali Hossein Khani and Gary Kemp , 1st ed., Routledge.' short: 'N. Milkov, in: A.H. Khani , G. Kemp (Eds.), Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 Vol., Volume II, 1st ed., Routledge, London, n.d.' date_created: 2025-02-24T18:33:50Z date_updated: 2025-02-24T18:38:38Z department: - _id: '14' edition: '1' editor: - first_name: 'Ali Hossein ' full_name: 'Khani , Ali Hossein ' last_name: 'Khani ' - first_name: 'Gary ' full_name: 'Kemp , Gary ' last_name: 'Kemp ' keyword: - elucidation - facts - Frege - language - metaphysics - G. E. Moore - Russell - Stebbing - John Wisdom - Wittgenstein language: - iso: eng place: London publication: 'Wittgenstein and Other Philosophers: His Influence on Historical and Contemporary Analytic Philosophers, 2 vol., Volume II' publication_status: inpress publisher: Routledge quality_controlled: '1' status: public title: Wisdom's Wittgenstein type: book_chapter user_id: '357' year: '2025' ... --- _id: '58885' abstract: - lang: eng text: 'There have been several attempts to conceptualize and operationalize pedagogical content knowledge (PCK) in the context of teachers'' professional competencies. A recent and popular model is the Refined Consensus Model (RCM), which proposes a framework of dispositional competencies (personal PCK—pPCK) that influence more action-related competencies (enacted PCK—ePCK) and vice versa. However, descriptions of the internal structure of pPCK and possible knowledge domains that might develop independently are still limited, being either primarily theoretically motivated or strictly hierarchical and therefore of limited use, for example, for formative feedback and further development of the RCM. Meanwhile, a non-hierarchical differentiation for the ePCK regarding the plan-teach-reflect cycle has emerged. In this study, we present an exploratory computational approach to investigate pre-service teachers'' pPCK for a similar non-hierarchical structure using a large dataset of responses to a pPCK questionnaire (N=846). We drew on theoretical foundations and previous empirical findings to achieve interpretability by integrating this external knowledge into our analyses using the Computational Grounded Theory (CGT) framework. The results of a cluster analysis of the pPCK scores indicate the emergence of prototypical groups, which we refer to as competency profiles: (1) a group with low performance, (2) a group with relatively advanced competency in using pPCK to create instructional elements, (3) a group with relatively advanced competency in using pPCK to assess and analyze described instructional elements, and (4) a group with high performance. These groups show tendencies for certain language usage, which we analyze using a structural topic model in a CGT-inspired pattern refinement step. We verify these patterns by demonstrating the ability of a machine learning model to predict the competency profile assignments. Finally, we discuss some implications of the results for the further development of the RCM and their potential usability for an automated formative assessment.' article_type: original author: - first_name: Jannis full_name: Zeller, Jannis id: '99022' last_name: Zeller orcid: 0000-0002-1834-5520 - first_name: Josef full_name: Riese, Josef id: '429' last_name: Riese orcid: 0000-0003-2927-2619 citation: ama: 'Zeller J, Riese J. Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses? Journal of Research in Science Teaching. Published online 2025. doi:10.1002/tea.70001' apa: 'Zeller, J., & Riese, J. (2025). Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses? Journal of Research in Science Teaching. https://doi.org/10.1002/tea.70001' bibtex: '@article{Zeller_Riese_2025, title={Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses?}, DOI={10.1002/tea.70001}, journal={Journal of Research in Science Teaching}, author={Zeller, Jannis and Riese, Josef}, year={2025} }' chicago: 'Zeller, Jannis, and Josef Riese. “Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of PPCK Emerge From Non-Hierarchical Analyses?” Journal of Research in Science Teaching, 2025. https://doi.org/10.1002/tea.70001.' ieee: 'J. Zeller and J. Riese, “Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses?,” Journal of Research in Science Teaching, 2025, doi: 10.1002/tea.70001.' mla: 'Zeller, Jannis, and Josef Riese. “Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of PPCK Emerge From Non-Hierarchical Analyses?” Journal of Research in Science Teaching, 2025, doi:10.1002/tea.70001.' short: J. Zeller, J. Riese, Journal of Research in Science Teaching (2025). date_created: 2025-03-04T08:08:37Z date_updated: 2025-03-04T08:08:42Z department: - _id: '299' doi: 10.1002/tea.70001 keyword: - computational grounded theory - language analysis - machine learning - pedagogical content knowledge - unsupervised learning language: - iso: eng main_file_link: - open_access: '1' url: https://onlinelibrary.wiley.com/doi/epdf/10.1002/tea.70001 oa: '1' publication: Journal of Research in Science Teaching publication_identifier: eissn: - 1098-2736 issn: - 0022-4308 publication_status: published status: public title: 'Competency Profiles of PCK Using Unsupervised Learning: What Implications for the Structures of pPCK Emerge From Non-Hierarchical Analyses?' type: journal_article user_id: '99022' year: '2025' ... --- _id: '60958' abstract: - lang: eng text: Large Language Models (LLMs) excel in understanding, generating, and processing human language, with growing adoption in process mining. Process mining relies on event logs that capture explicit process knowledge; however, knowledge-intensive processes (KIPs) in domains such as healthcare and product development depend on tacit knowledge, which is often absent from event logs. To bridge this gap, this study proposes a LLM-based framework for mobilizing tacit process knowledge and enriching event logs. A proof-of-concept is demonstrated using a KIP-specific LLM-driven conversational agent built on GPT-4o. The results indicate that LLMs can capture tacit process knowledge through targeted queries and systematically integrate it into event logs. This study presents a novel approach combining LLMs, knowledge management, and process mining, advancing the understanding and management of KIPs by enhancing knowledge accessibility and documentation. author: - first_name: Katharina full_name: Brennig, Katharina last_name: Brennig citation: ama: 'Brennig K. Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes. In: AMCIS 2025 Proceedings. 11. ; 2025.' apa: 'Brennig, K. (2025). Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes. AMCIS 2025 Proceedings. 11. Americas Conference on Information Systems, Montréal.' bibtex: '@inproceedings{Brennig_2025, title={Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes}, booktitle={AMCIS 2025 Proceedings. 11.}, author={Brennig, Katharina}, year={2025} }' chicago: 'Brennig, Katharina. “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes.” In AMCIS 2025 Proceedings. 11., 2025.' ieee: 'K. Brennig, “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes,” presented at the Americas Conference on Information Systems, Montréal, 2025.' mla: 'Brennig, Katharina. “Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes.” AMCIS 2025 Proceedings. 11., 2025.' short: 'K. Brennig, in: AMCIS 2025 Proceedings. 11., 2025.' conference: end_date: 2025-08-16 location: Montréal name: Americas Conference on Information Systems start_date: 2025-08-14 date_created: 2025-08-20T07:03:37Z date_updated: 2025-08-20T07:06:16Z department: - _id: '196' keyword: - Process Mining - Large Language Model - Knowledge Management - Knowledge-Intensive Process - Tacit Knowledge language: - iso: eng main_file_link: - url: https://aisel.aisnet.org/amcis2025/sig_svc/sig_svc/11/ publication: AMCIS 2025 Proceedings. 11. related_material: link: - relation: confirmation url: https://aisel.aisnet.org/amcis2025/sig_svc/sig_svc/11/ status: public title: 'Revealing the Unspoken: Using LLMs to Mobilize and Enrich Tacit Knowledge in Event Logs of Knowledge-Intensive Processes' type: conference user_id: '51905' year: '2025' ... --- _id: '62701' 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.' author: - first_name: Caglar full_name: Demir, Caglar last_name: Demir - first_name: Moshood full_name: Yekini, Moshood last_name: Yekini - first_name: Michael full_name: Röder, Michael last_name: Röder - first_name: Yasir full_name: Mahmood, Yasir last_name: Mahmood - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille last_name: Ngonga Ngomo citation: ama: 'Demir C, Yekini M, Röder M, Mahmood Y, Ngonga Ngomo A-C. Tree-Based OWL Class Expression Learner over Large Graphs. In: Lecture Notes in Computer Science. Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-06066-2_29' apa: Demir, C., Yekini, M., Röder, M., Mahmood, Y., & Ngonga Ngomo, A.-C. (2025). Tree-Based OWL Class Expression Learner over Large Graphs. In Lecture Notes in Computer Science. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML PKDD, Porto, Portugal. Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-06066-2_29 bibtex: '@inbook{Demir_Yekini_Röder_Mahmood_Ngonga Ngomo_2025, place={Cham}, title={Tree-Based OWL Class Expression Learner over Large Graphs}, DOI={10.1007/978-3-032-06066-2_29}, 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} }' chicago: 'Demir, Caglar, Moshood Yekini, Michael Röder, Yasir Mahmood, and Axel-Cyrille Ngonga Ngomo. “Tree-Based OWL Class Expression Learner over Large Graphs.” In Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-032-06066-2_29.' ieee: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, and A.-C. Ngonga Ngomo, “Tree-Based OWL Class Expression Learner over Large Graphs,” in Lecture Notes in Computer Science, Cham: Springer Nature Switzerland, 2025.' mla: Demir, Caglar, et al. “Tree-Based OWL Class Expression Learner over Large Graphs.” Lecture Notes in Computer Science, Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-06066-2_29. short: 'C. Demir, M. Yekini, M. Röder, Y. Mahmood, A.-C. Ngonga Ngomo, in: Lecture Notes in Computer Science, Springer Nature Switzerland, Cham, 2025.' 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 date_created: 2025-11-28T14:09:17Z date_updated: 2025-11-28T14:57:39Z department: - _id: '34' - _id: '574' doi: 10.1007/978-3-032-06066-2_29 keyword: - Decision Tree - OWL Class Expression Learning - Description Logic - Knowledge Graph - Large Language Model - Verbalizer language: - iso: eng place: Cham project: - _id: '285' name: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen publication: Lecture Notes in Computer Science publication_identifier: isbn: - '9783032060655' - '9783032060662' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer Nature Switzerland status: public title: Tree-Based OWL Class Expression Learner over Large Graphs type: book_chapter user_id: '114533' year: '2025' ... --- _id: '57892' abstract: - lang: eng text: 'The present paper discusses the extent to which Large Language Models (LLMs) may affect the scientific enterprise, reinforcing or mitigating existing structural inequalities expressed by the Matthew Effect and introducing a “bot delusion” in academia. In a theory-led thought experiment, we first focus on the academic publication and citation system and develop three scenarios of the anticipated consequences of using LLMs: reproducing content and status quo (Scenario 1), enabling content coherence evaluation (Scenario 2) and content evaluation (Scenario 3). Second, we discuss the interaction between the use of LLMs and academic (counter)norms for citation selection and their impact on the publication and citation system. Finally, we introduce communal counter-norms to capture academics’ loyal citation behavior and develop three future scenarios that academia may face when LLMs are widely used in the research process, namely status quo future of science, mixed-access future, and open science future.' article_number: '103537' article_type: original author: - first_name: Oliver full_name: Wieczorek, Oliver last_name: Wieczorek - first_name: Isabel full_name: Steinhardt, Isabel id: '90339' last_name: Steinhardt orcid: https://orcid.org/0000-0002-2590-6189 - first_name: Rebecca full_name: Schmidt, Rebecca id: '94416' last_name: Schmidt orcid: https://orcid.org/0000-0002-2516-359X - first_name: Sylvi full_name: Mauermeister, Sylvi id: '98032' last_name: Mauermeister - first_name: Christian full_name: Schneijderberg, Christian last_name: Schneijderberg citation: ama: Wieczorek O, Steinhardt I, Schmidt R, Mauermeister S, Schneijderberg C. The Bot Delusion. Large language models and anticipated consequences for academics’ publication and citation behavior. Futures. 2024;166. doi:10.1016/j.futures.2024.103537 apa: Wieczorek, O., Steinhardt, I., Schmidt, R., Mauermeister, S., & Schneijderberg, C. (2024). The Bot Delusion. Large language models and anticipated consequences for academics’ publication and citation behavior. Futures, 166, Article 103537. https://doi.org/10.1016/j.futures.2024.103537 bibtex: '@article{Wieczorek_Steinhardt_Schmidt_Mauermeister_Schneijderberg_2024, title={The Bot Delusion. Large language models and anticipated consequences for academics’ publication and citation behavior}, volume={166}, DOI={10.1016/j.futures.2024.103537}, number={103537}, journal={Futures}, publisher={Elsevier BV}, author={Wieczorek, Oliver and Steinhardt, Isabel and Schmidt, Rebecca and Mauermeister, Sylvi and Schneijderberg, Christian}, year={2024} }' chicago: Wieczorek, Oliver, Isabel Steinhardt, Rebecca Schmidt, Sylvi Mauermeister, and Christian Schneijderberg. “The Bot Delusion. Large Language Models and Anticipated Consequences for Academics’ Publication and Citation Behavior.” Futures 166 (2024). https://doi.org/10.1016/j.futures.2024.103537. ieee: 'O. Wieczorek, I. Steinhardt, R. Schmidt, S. Mauermeister, and C. Schneijderberg, “The Bot Delusion. Large language models and anticipated consequences for academics’ publication and citation behavior,” Futures, vol. 166, Art. no. 103537, 2024, doi: 10.1016/j.futures.2024.103537.' mla: Wieczorek, Oliver, et al. “The Bot Delusion. Large Language Models and Anticipated Consequences for Academics’ Publication and Citation Behavior.” Futures, vol. 166, 103537, Elsevier BV, 2024, doi:10.1016/j.futures.2024.103537. short: O. Wieczorek, I. Steinhardt, R. Schmidt, S. Mauermeister, C. Schneijderberg, Futures 166 (2024). date_created: 2024-12-31T08:30:51Z date_updated: 2024-12-31T08:36:28Z department: - _id: '121' doi: 10.1016/j.futures.2024.103537 intvolume: ' 166' keyword: - Large Language Models - Matthew Effect - Academic Publishing and Citation Systems - Scientific Norms - Thought Experiment language: - iso: eng main_file_link: - open_access: '1' url: https://www.sciencedirect.com/science/article/pii/S0016328724002209?via%3Dihub oa: '1' publication: Futures publication_identifier: issn: - 0016-3287 publication_status: published publisher: Elsevier BV quality_controlled: '1' status: public title: The Bot Delusion. Large language models and anticipated consequences for academics’ publication and citation behavior type: journal_article user_id: '90339' volume: 166 year: '2024' ... --- _id: '51270' abstract: - lang: eng text: This study investigates the teaching methods that future teachers of German as a foreign language use in cultural mediation. Utilizing a qualitative and hermeneutic approach, it analyzes data from a teacher-training module of the International Master's in German as a Foreign/Second Language that Friedrich Schiller University Jena in Germany offers. Participants taught an online course to students from a Japanese university, which focused on cultural learning. Within the teacher training module, the participants discussed their lesson plans, conducted classes, and subsequently reflected on their teaching practices by exploring and critiquing the practical application of their teaching skills. The analysis, which was conducted using qualitative evaluative content analysis following Kuckartz's (2018) approach, revealed a preference for distributive/instructive methods, with some recognition of interactive and collaborative methods. A tendency towards both repetitive and reflective practices was evident, with a predominant focus on content that was specific to a supposed target culture rather than intercultural or transcultural content. The study highlights the need to balance knowledge transmission with the development of critical and reflective skills in cultural mediation. It emphasizes the importance of incorporating collaborative and interactive methods, which promote a critical attitude that is necessary in language teachers and learners. In conclusion, this study advocates adaptive and reflective teaching as an essential component in the training of future language teachers in globalized contexts. alternative_title: - Methods of cultural mediation in the practical training of fute teachers of German as a Foreign Language article_type: original author: - first_name: Alexandra full_name: Treder, Alexandra id: '95412' last_name: Treder orcid: 0009-0003-9045-5964 citation: ama: Treder A. Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera. Revista Lengua y Cultura. 2024;5(10):56–68. doi:https://doi.org/10.29057/lc.v5i10.12379 apa: Treder, A. (2024). Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera. Revista Lengua y Cultura, 5(10), 56–68. https://doi.org/10.29057/lc.v5i10.12379 bibtex: '@article{Treder_2024, title={Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera}, volume={5}, DOI={https://doi.org/10.29057/lc.v5i10.12379}, number={10}, journal={Revista Lengua y Cultura}, publisher={Universidad Autónoma del Estado de Hidalgo, Mexico}, author={Treder, Alexandra}, year={2024}, pages={56–68} }' chicago: 'Treder, Alexandra. “Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera.” Revista Lengua y Cultura 5, no. 10 (2024): 56–68. https://doi.org/10.29057/lc.v5i10.12379.' ieee: 'A. Treder, “Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera,” Revista Lengua y Cultura, vol. 5, no. 10, pp. 56–68, 2024, doi: https://doi.org/10.29057/lc.v5i10.12379.' mla: Treder, Alexandra. “Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera.” Revista Lengua y Cultura, vol. 5, no. 10, Universidad Autónoma del Estado de Hidalgo, Mexico, 2024, pp. 56–68, doi:https://doi.org/10.29057/lc.v5i10.12379. short: A. Treder, Revista Lengua y Cultura 5 (2024) 56–68. date_created: 2024-02-08T08:12:25Z date_updated: 2025-02-07T13:44:53Z department: - _id: '937' doi: https://doi.org/10.29057/lc.v5i10.12379 intvolume: ' 5' issue: '10' keyword: - cultural mediation - teacher training - foreign language teaching - teaching methods - teaching practice language: - iso: spa main_file_link: - open_access: '1' url: https://repository.uaeh.edu.mx/revistas/index.php/lc/article/view/12379/11161 oa: '1' page: 56–68 publication: Revista Lengua y Cultura publication_status: published publisher: Universidad Autónoma del Estado de Hidalgo, Mexico quality_controlled: '1' status: public title: Métodos de la mediación de cultura en el entrenamiento práctico de futuros/as profesores/as de Alemán como Lengua Extranjera type: journal_article user_id: '95412' volume: 5 year: '2024' ... --- _id: '56983' abstract: - lang: eng text: Detecting the veracity of a statement automatically is a challenge the world is grappling with due to the vast amount of data spread across the web. Verifying a given claim typically entails validating it within the framework of supporting evidence like a retrieved piece of text. Classifying the stance of the text with respect to the claim is called stance classification. Despite advancements in automated fact-checking, most systems still rely on a substantial quantity of labeled training data, which can be costly. In this work, we avoid the costly training or fine-tuning of models by reusing pre-trained large language models together with few-shot in-context learning. Since we do not train any model, our approach ExPrompt is lightweight, demands fewer resources than other stance classification methods and can serve as a modern baseline for future developments. At the same time, our evaluation shows that our approach is able to outperform former state-of-the-art stance classification approaches regarding accuracy by at least 2 percent. Our scripts and data used in this paper are available at https://github.com/dice-group/ExPrompt. author: - first_name: Umair full_name: Qudus, Umair id: '83392' last_name: Qudus orcid: 0000-0001-6714-8729 - first_name: Michael full_name: Röder, Michael id: '67199' last_name: Röder orcid: https://orcid.org/0000-0002-8609-8277 - first_name: Daniel full_name: Vollmers, Daniel last_name: Vollmers - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'Qudus U, Röder M, Vollmers D, Ngonga Ngomo A-C. ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Vol 9. ACM; 2024:3994-3999. doi:10.1145/3627673.3679923' apa: 'Qudus, U., Röder, M., Vollmers, D., & Ngonga Ngomo, A.-C. (2024). ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 9, 3994–3999. https://doi.org/10.1145/3627673.3679923' bibtex: '@inproceedings{Qudus_Röder_Vollmers_Ngonga Ngomo_2024, title={ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification}, volume={9}, DOI={10.1145/3627673.3679923}, booktitle={Proceedings of the 33rd ACM International Conference on Information and Knowledge Management}, publisher={ACM}, author={Qudus, Umair and Röder, Michael and Vollmers, Daniel and Ngonga Ngomo, Axel-Cyrille}, year={2024}, pages={3994–3999} }' chicago: 'Qudus, Umair, Michael Röder, Daniel Vollmers, and Axel-Cyrille Ngonga Ngomo. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 9:3994–99. ACM, 2024. https://doi.org/10.1145/3627673.3679923.' ieee: 'U. Qudus, M. Röder, D. Vollmers, and A.-C. Ngonga Ngomo, “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification,” in Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, Boise, ID, USA, 2024, vol. 9, pp. 3994–3999, doi: 10.1145/3627673.3679923.' mla: 'Qudus, Umair, et al. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, vol. 9, ACM, 2024, pp. 3994–99, doi:10.1145/3627673.3679923.' short: 'U. Qudus, M. Röder, D. Vollmers, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, ACM, 2024, pp. 3994–3999.' conference: end_date: 2024-10-25 location: Boise, ID, USA name: 'CIKM ''24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management' start_date: 2024-10-21 date_created: 2024-11-11T13:15:25Z date_updated: 2025-09-11T09:49:07Z ddc: - '006' doi: 10.1145/3627673.3679923 file: - access_level: closed content_type: application/pdf creator: uqudus date_created: 2024-11-11T13:24:19Z date_updated: 2024-11-11T13:24:19Z file_id: '56984' file_name: public.pdf file_size: 531579 relation: main_file success: 1 file_date_updated: 2024-11-11T13:24:19Z has_accepted_license: '1' intvolume: ' 9' keyword: - Stance Classification - Few-shot in-context learning - Pre-trained large language models language: - iso: eng main_file_link: - url: https://dl.acm.org/doi/10.1145/3627673.3679923 page: 3994 - 3999 popular_science: '1' project: - _id: '412' name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen' publication: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management publication_identifier: isbn: - 79-8-4007-0436-9/24/10 publication_status: published publisher: ACM quality_controlled: '1' status: public title: 'ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification' type: conference user_id: '83392' volume: 9 year: '2024' ... --- _id: '53801' abstract: - lang: eng text: 'In this study, we evaluate the impact of gender-biased data from German-language physician reviews on the fairness of fine-tuned language models. For two different downstream tasks, we use data reported to be gender biased and aggregate it with annotations. First, we propose a new approach to aspect-based sentiment analysis that allows identifying, extracting, and classifying implicit and explicit aspect phrases and their polarity within a single model. The second task we present is grade prediction, where we predict the overall grade of a review on the basis of the review text. For both tasks, we train numerous transformer models and evaluate their performance. The aggregation of sensitive attributes, such as a physician’s gender and migration background, with individual text reviews allows us to measure the performance of the models with respect to these sensitive groups. These group-wise performance measures act as extrinsic bias measures for our downstream tasks. In addition, we translate several gender-specific templates of the intrinsic bias metrics into the German language and evaluate our fine-tuned models. Based on this set of tasks, fine-tuned models, and intrinsic and extrinsic bias measures, we perform correlation analyses between intrinsic and extrinsic bias measures. In terms of sensitive groups and effect sizes, our bias measure results show different directions. Furthermore, correlations between measures of intrinsic and extrinsic bias can be observed in different directions. This leads us to conclude that gender-biased data does not inherently lead to biased models. Other variables, such as template dependency for intrinsic measures and label distribution in the data, must be taken into account as they strongly influence the metric results. Therefore, we suggest that metrics and templates should be chosen according to the given task and the biases to be assessed. ' article_number: '102235' article_type: original author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Falk full_name: Maoro, Falk last_name: Maoro - first_name: Michaela full_name: Geierhos, Michaela last_name: Geierhos citation: ama: 'Kersting J, Maoro F, Geierhos M. Towards comparable ratings: Exploring bias in German physician reviews. Data & Knowledge Engineering. 2023;148. doi:10.1016/j.datak.2023.102235' apa: 'Kersting, J., Maoro, F., & Geierhos, M. (2023). Towards comparable ratings: Exploring bias in German physician reviews. Data & Knowledge Engineering, 148, Article 102235. https://doi.org/10.1016/j.datak.2023.102235' bibtex: '@article{Kersting_Maoro_Geierhos_2023, title={Towards comparable ratings: Exploring bias in German physician reviews}, volume={148}, DOI={10.1016/j.datak.2023.102235}, number={102235}, journal={Data & Knowledge Engineering}, publisher={Elsevier}, author={Kersting, Joschka and Maoro, Falk and Geierhos, Michaela}, year={2023} }' chicago: 'Kersting, Joschka, Falk Maoro, and Michaela Geierhos. “Towards Comparable Ratings: Exploring Bias in German Physician Reviews.” Data & Knowledge Engineering 148 (2023). https://doi.org/10.1016/j.datak.2023.102235.' ieee: 'J. Kersting, F. Maoro, and M. Geierhos, “Towards comparable ratings: Exploring bias in German physician reviews,” Data & Knowledge Engineering, vol. 148, Art. no. 102235, 2023, doi: 10.1016/j.datak.2023.102235.' mla: 'Kersting, Joschka, et al. “Towards Comparable Ratings: Exploring Bias in German Physician Reviews.” Data & Knowledge Engineering, vol. 148, 102235, Elsevier, 2023, doi:10.1016/j.datak.2023.102235.' short: J. Kersting, F. Maoro, M. Geierhos, Data & Knowledge Engineering 148 (2023). date_created: 2024-04-30T12:30:56Z date_updated: 2024-04-30T12:41:14Z ddc: - '004' department: - _id: '579' doi: 10.1016/j.datak.2023.102235 file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2024-04-30T12:34:35Z date_updated: 2024-04-30T12:34:35Z file_id: '53802' file_name: Kersting 2023.pdf file_size: 1381398 relation: main_file success: 1 file_date_updated: 2024-04-30T12:34:35Z funded_apc: '1' has_accepted_license: '1' intvolume: ' 148' keyword: - Language model fairness - Aspect phrase classification - Grade prediction - Physician reviews language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.1016/j.datak.2023.102235 ' oa: '1' project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Parametrisierte Servicespezifikation (Subproject B1)' publication: Data & Knowledge Engineering publication_identifier: issn: - 0169-023X publication_status: published publisher: Elsevier status: public title: 'Towards comparable ratings: Exploring bias in German physician reviews' type: journal_article user_id: '58701' volume: 148 year: '2023' ... --- _id: '52865' abstract: - lang: eng text: This paper addresses new challenges of detecting campaigns in social media, which emerged with the rise of Large Language Models (LLMs). LLMs particularly challenge algorithms focused on the temporal analysis of topical clusters. Simple similarity measures can no longer capture and map campaigns that were previously broadly similar in content. Herein, we analyze whether the classification of messages over time can be profitably used to rediscover poorly detectable campaigns at the content level. Thus, we evaluate classical classifiers and a new method based on siamese neural networks. Our results show that campaigns can be detected despite the limited reliability of the classifiers as long as they are based on a large amount of simultaneously spread artificial content. author: - first_name: Britta full_name: Grimme, Britta last_name: Grimme - first_name: Janina full_name: Pohl, Janina last_name: Pohl - first_name: Hendrik full_name: Winkelmann, Hendrik last_name: Winkelmann - first_name: Lucas full_name: Stampe, Lucas last_name: Stampe - first_name: Christian full_name: Grimme, Christian last_name: Grimme citation: ama: 'Grimme B, Pohl J, Winkelmann H, Stampe L, Grimme C. Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media. In: Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings. Springer-Verlag; 2023:72–87. doi:10.1007/978-3-031-47896-3_6' apa: 'Grimme, B., Pohl, J., Winkelmann, H., Stampe, L., & Grimme, C. (2023). Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media. Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings, 72–87. https://doi.org/10.1007/978-3-031-47896-3_6' bibtex: '@inproceedings{Grimme_Pohl_Winkelmann_Stampe_Grimme_2023, place={Berlin, Heidelberg}, title={Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media}, DOI={10.1007/978-3-031-47896-3_6}, booktitle={Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings}, publisher={Springer-Verlag}, author={Grimme, Britta and Pohl, Janina and Winkelmann, Hendrik and Stampe, Lucas and Grimme, Christian}, year={2023}, pages={72–87} }' chicago: 'Grimme, Britta, Janina Pohl, Hendrik Winkelmann, Lucas Stampe, and Christian Grimme. “Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media.” In Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings, 72–87. Berlin, Heidelberg: Springer-Verlag, 2023. https://doi.org/10.1007/978-3-031-47896-3_6.' ieee: 'B. Grimme, J. Pohl, H. Winkelmann, L. Stampe, and C. Grimme, “Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media,” in Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings, 2023, pp. 72–87, doi: 10.1007/978-3-031-47896-3_6.' mla: 'Grimme, Britta, et al. “Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media.” Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings, Springer-Verlag, 2023, pp. 72–87, doi:10.1007/978-3-031-47896-3_6.' short: 'B. Grimme, J. Pohl, H. Winkelmann, L. Stampe, C. Grimme, in: Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings, Springer-Verlag, Berlin, Heidelberg, 2023, pp. 72–87.' date_created: 2024-03-25T14:38:01Z date_updated: 2026-03-19T07:48:51Z doi: 10.1007/978-3-031-47896-3_6 keyword: - Social Media - Campaign Detection - Large Language Models - Siamese Neural Networks page: 72–87 place: Berlin, Heidelberg publication: 'Disinformation in Open Online Media: 5th Multidisciplinary International Symposium, MISDOOM 2023, Amsterdam, The Netherlands, November 21–22, 2023, Proceedings' publication_identifier: isbn: - 978-3-031-47895-6 publisher: Springer-Verlag status: public title: 'Lost in Transformation: Rediscovering LLM-Generated Campaigns in Social Media' type: conference user_id: '103682' year: '2023' ... --- _id: '27507' abstract: - lang: eng text: Accurate real estate appraisal is essential in decision making processes of financial institutions, governments, and trending real estate platforms like Zillow. One of the most important factors of a property’s value is its location. However, creating accurate quantifications of location remains a challenge. While traditional approaches rely on Geographical Information Systems (GIS), recently unstructured data in form of images was incorporated in the appraisal process, but text data remains an untapped reservoir. Our study shows that using text data in form of geolocated Wikipedia articles can increase predictive performance over traditional GIS-based methods by 8.2% in spatial out-of-sample validation. A framework to automatically extract geographically weighted vector representations for text is established and used alongside traditional structural housing features to make predictions and to uncover local patterns on sale price for real estate transactions between 2015 and 2020 in Allegheny County, Pennsylvania. author: - first_name: Tim full_name: Heuwinkel, Tim last_name: Heuwinkel - first_name: Jan-Peter full_name: Kucklick, Jan-Peter id: '77066' last_name: Kucklick - first_name: Oliver full_name: Müller, Oliver id: '72849' last_name: Müller citation: ama: 'Heuwinkel T, Kucklick J-P, Müller O. Using Geolocated Text to Quantify Location in Real Estate Appraisal. In: 55th Annual Hawaii International Conference on System Sciences (HICSS-55). ; 2022.' apa: Heuwinkel, T., Kucklick, J.-P., & Müller, O. (2022). Using Geolocated Text to Quantify Location in Real Estate Appraisal. 55th Annual Hawaii International Conference on System Sciences (HICSS-55). Hawaii International Conference on System Science (HICSS), Virtual. bibtex: '@inproceedings{Heuwinkel_Kucklick_Müller_2022, title={Using Geolocated Text to Quantify Location in Real Estate Appraisal}, booktitle={55th Annual Hawaii International Conference on System Sciences (HICSS-55)}, author={Heuwinkel, Tim and Kucklick, Jan-Peter and Müller, Oliver}, year={2022} }' chicago: Heuwinkel, Tim, Jan-Peter Kucklick, and Oliver Müller. “Using Geolocated Text to Quantify Location in Real Estate Appraisal.” In 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022. ieee: T. Heuwinkel, J.-P. Kucklick, and O. Müller, “Using Geolocated Text to Quantify Location in Real Estate Appraisal,” presented at the Hawaii International Conference on System Science (HICSS), Virtual, 2022. mla: Heuwinkel, Tim, et al. “Using Geolocated Text to Quantify Location in Real Estate Appraisal.” 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022. short: 'T. Heuwinkel, J.-P. Kucklick, O. Müller, in: 55th Annual Hawaii International Conference on System Sciences (HICSS-55), 2022.' conference: end_date: 2022-01-07 location: Virtual name: Hawaii International Conference on System Science (HICSS) start_date: 2022-01-03 date_created: 2021-11-17T07:12:03Z date_updated: 2022-01-06T06:57:40Z department: - _id: '195' keyword: - Real Estate Appraisal - Text Regression - Natural Language Processing (NLP) - Location Intelligence - Wikipedia language: - iso: eng main_file_link: - open_access: '1' url: https://scholarspace.manoa.hawaii.edu/bitstream/10125/80039/0561.pdf oa: '1' publication: 55th Annual Hawaii International Conference on System Sciences (HICSS-55) status: public title: Using Geolocated Text to Quantify Location in Real Estate Appraisal type: conference user_id: '77066' year: '2022' ... --- _id: '31054' abstract: - lang: eng text: This paper aims at discussing past limitations set in sentiment analysis research regarding explicit and implicit mentions of opinions. Previous studies have regularly neglected this question in favor of methodical research on standard-datasets. Furthermore, they were limited to linguistically less-diverse domains, such as commercial product reviews. We face this issue by annotating a German-language physician review dataset that contains numerous implicit, long, and complex statements that indicate aspect ratings, such as the physician’s friendliness. We discuss the nature of implicit statements and present various samples to illustrate the challenge described. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer citation: ama: 'Kersting J, Bäumer FS. Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis. In: Kersting J, ed. Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications. IARIA; 2022:5-9.' apa: 'Kersting, J., & Bäumer, F. S. (2022). Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis. In J. Kersting (Ed.), Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications (pp. 5–9). IARIA.' bibtex: '@inproceedings{Kersting_Bäumer_2022, place={Barcelona, Spain}, title={Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis}, booktitle={Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications}, publisher={IARIA}, author={Kersting, Joschka and Bäumer, Frederik Simon}, editor={Kersting, Joschka}, year={2022}, pages={5–9} }' chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis.” In Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, edited by Joschka Kersting, 5–9. Barcelona, Spain: IARIA, 2022.' ieee: 'J. Kersting and F. S. Bäumer, “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis,” in Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, Barcelona, Spain, 2022, pp. 5–9.' mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis.” Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, edited by Joschka Kersting, IARIA, 2022, pp. 5–9.' short: 'J. Kersting, F.S. Bäumer, in: J. Kersting (Ed.), Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications, IARIA, Barcelona, Spain, 2022, pp. 5–9.' conference: location: Barcelona, Spain name: The Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022) start_date: 2022-03 date_created: 2022-05-04T08:12:09Z date_updated: 2022-12-01T13:40:11Z ddc: - '006' editor: - first_name: Joschka full_name: Kersting, Joschka last_name: Kersting file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2022-12-01T13:39:48Z date_updated: 2022-12-01T13:39:48Z file_id: '34172' file_name: Kersting & Bäumer (2022), Kersting2022.pdf file_size: 155548 relation: main_file success: 1 file_date_updated: 2022-12-01T13:39:48Z has_accepted_license: '1' keyword: - Sentiment analysis - Natural language processing - Aspect phrase extraction language: - iso: eng page: 5-9 place: Barcelona, Spain project: - _id: '1' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' name: 'SFB 901 - B1: SFB 901 - Subproject B1' publication: 'Proceedings of the Fourteenth International Conference on Pervasive Patterns and Applications (PATTERNS 2022): Special Track AI-DRSWA: Maturing Artificial Intelligence - Data Science for Real-World Applications' publication_status: published publisher: IARIA status: public title: 'Implicit Statements in Healthcare Reviews: A Challenge for Sentiment Analysis' type: conference user_id: '58701' year: '2022' ... --- _id: '28349' abstract: - lang: ger text: "Das Auftreten der COVID-19-Pandemie stellt Fremdsprachenkurse vielerorts vor Herausforderungen. Unter Zuhilfenahme diverser digitaler Tools werden nicht nur Lernmaterialien online geteilt, sondern auch die Interaktion zwischen Lehrenden und Lernenden sowie der Lernenden untereinander in den virtuellen Raum verlagert. Qualitative Interviews mit den Beteiligten erfassen, wie diese mit den Herausforderungen videogestützten Sprachunterrichts umgehen und welche Strategien sie wählen, um Sprachenlernen zu ermöglichen. Die Ergebnisse zeigen auf, wo seitens der Kursorganisation und -durchführung Handlungsbedarf besteht.\r\n-----\r\nThe rise of the COVID-19 pandemic challenges the teaching and learning of foreign languages at many institutions. The implementation of various digital tools aids not only the online sharing of learning materials, but also shifts teacher-learner and learner-learner interaction to the virtual space. Via qualitative interviews, this study examines how both teachers and learners handle the challenges of language instruction based on videoconferences, and what strategies they employ to enable language learning. The results highlight areas in need of improvement in terms of course organization and facilitation." article_type: original author: - first_name: Sandra full_name: Drumm, Sandra last_name: Drumm - first_name: Mareike full_name: Müller, Mareike id: '71540' last_name: Müller - first_name: Nadja full_name: Stenzel, Nadja last_name: Stenzel citation: ama: 'Drumm S, Müller M, Stenzel N. Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie. Informationen Deutsch als Fremdsprache. 2021;48(5):496-515. doi:10.1515/infodaf-2021-0069' apa: 'Drumm, S., Müller, M., & Stenzel, N. (2021). Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie. Informationen Deutsch als Fremdsprache, 48(5), 496–515. https://doi.org/10.1515/infodaf-2021-0069' bibtex: '@article{Drumm_Müller_Stenzel_2021, title={Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie}, volume={48}, DOI={10.1515/infodaf-2021-0069}, number={5}, journal={Informationen Deutsch als Fremdsprache}, author={Drumm, Sandra and Müller, Mareike and Stenzel, Nadja}, year={2021}, pages={496–515} }' chicago: 'Drumm, Sandra, Mareike Müller, and Nadja Stenzel. “Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie.” Informationen Deutsch als Fremdsprache 48, no. 5 (2021): 496–515. https://doi.org/10.1515/infodaf-2021-0069.' ieee: 'S. Drumm, M. Müller, and N. Stenzel, “Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie,” Informationen Deutsch als Fremdsprache, vol. 48, no. 5, pp. 496–515, 2021, doi: 10.1515/infodaf-2021-0069.' mla: 'Drumm, Sandra, et al. “Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie.” Informationen Deutsch als Fremdsprache, vol. 48, no. 5, 2021, pp. 496–515, doi:10.1515/infodaf-2021-0069.' short: S. Drumm, M. Müller, N. Stenzel, Informationen Deutsch als Fremdsprache 48 (2021) 496–515. date_created: 2021-12-07T10:32:28Z date_updated: 2022-01-06T06:58:02Z department: - _id: '468' doi: 10.1515/infodaf-2021-0069 intvolume: ' 48' issue: '5' keyword: - German language courses at university - interaction - digital space - language learning/teaching via videoconference language: - iso: ger page: 496-515 publication: Informationen Deutsch als Fremdsprache publication_identifier: issn: - 2511-0853 - 0724-9616 publication_status: published status: public title: 'Digitale Räume geben und nehmen: Unterrichtsinteraktion in DSH-Kursen während der COVID-19-Pandemie' type: journal_article user_id: '71540' volume: 48 year: '2021' ... --- _id: '26049' abstract: - lang: eng text: 'Content is the new oil. Users consume billions of terabytes a day while surfing on news sites or blogs, posting on social media sites, and sending chat messages around the globe. While content is heterogeneous, the dominant form of web content is text. There are situations where more diversity needs to be introduced into text content, for example, to reuse it on websites or to allow a chatbot to base its models on the information conveyed rather than of the language used. In order to achieve this, paraphrasing techniques have been developed: One example is Text spinning, a technique that automatically paraphrases text while leaving the intent intact. This makes it easier to reuse content, or to change the language generated by the bot more human. One method for modifying texts is a combination of translation and back-translation. This paper presents NATTS, a naive approach that uses transformer-based translation models to create diversified text, combining translation steps in one model. An advantage of this approach is that it can be fine-tuned and handle technical language.' author: - first_name: Frederik Simon full_name: Bäumer, Frederik Simon last_name: Bäumer - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Sergej full_name: Denisov, Sergej last_name: Denisov - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Bäumer FS, Kersting J, Denisov S, Geierhos M. IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021. IADIS; 2021:221--225.' apa: 'Bäumer, F. S., Kersting, J., Denisov, S., & Geierhos, M. (2021). IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING. PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225.' bibtex: '@inproceedings{Bäumer_Kersting_Denisov_Geierhos_2021, title={IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING}, booktitle={PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021}, publisher={IADIS}, author={Bäumer, Frederik Simon and Kersting, Joschka and Denisov, Sergej and Geierhos, Michaela}, year={2021}, pages={221--225} }' chicago: 'Bäumer, Frederik Simon, Joschka Kersting, Sergej Denisov, and Michaela Geierhos. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.” In PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, 221--225. IADIS, 2021.' ieee: 'F. S. Bäumer, J. Kersting, S. Denisov, and M. Geierhos, “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, Lisbon, Portugal, 2021, pp. 221--225.' mla: 'Bäumer, Frederik Simon, et al. “IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING.” PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, IADIS, 2021, pp. 221--225.' short: 'F.S. Bäumer, J. Kersting, S. Denisov, M. Geierhos, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021, IADIS, 2021, pp. 221--225.' conference: end_date: 15.10.2021 location: Lisbon, Portugal name: 18th International Conference on Applied Computing start_date: 13.10.2021 date_created: 2021-10-11T15:26:58Z date_updated: 2022-01-06T06:57:16Z ddc: - '000' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2021-10-15T15:54:41Z date_updated: 2021-10-15T15:54:41Z file_id: '26282' file_name: Bäumer et al. (2021), Baeumer2021.pdf file_size: 411667 relation: main_file success: 1 file_date_updated: 2021-10-15T15:54:41Z has_accepted_license: '1' keyword: - Software Requirements - Natural Language Processing - Transfer Learning - On-The-Fly Computing language: - iso: eng page: 221--225 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: PROCEEDINGS OF THE INTERNATIONAL CONFERENCES ON WWW/INTERNET 2021 AND APPLIED COMPUTING 2021 publisher: IADIS status: public title: 'IN OTHER WORDS: A NAIVE APPROACH TO TEXT SPINNING' type: conference user_id: '58701' year: '2021' ... --- _id: '21727' abstract: - lang: eng text: 'Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems. ' author: - first_name: Christian full_name: Vorbohle, Christian id: '29951' last_name: Vorbohle - first_name: Sebastian full_name: Gottschalk, Sebastian id: '47208' last_name: Gottschalk citation: ama: 'Vorbohle C, Gottschalk S. Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems . In: Proceedings of the 29th European Conference on Information Systems (ECIS). AIS.' apa: 'Vorbohle, C., & Gottschalk, S. (n.d.). Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems . In Proceedings of the 29th European Conference on Information Systems (ECIS). Virtual Conference/Workshop: AIS.' bibtex: '@inproceedings{Vorbohle_Gottschalk, title={Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems }, booktitle={Proceedings of the 29th European Conference on Information Systems (ECIS)}, publisher={AIS}, author={Vorbohle, Christian and Gottschalk, Sebastian} }' chicago: Vorbohle, Christian, and Sebastian Gottschalk. “Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems .” In Proceedings of the 29th European Conference on Information Systems (ECIS). AIS, n.d. ieee: C. Vorbohle and S. Gottschalk, “Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems ,” in Proceedings of the 29th European Conference on Information Systems (ECIS), Virtual Conference/Workshop. mla: Vorbohle, Christian, and Sebastian Gottschalk. “Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems .” Proceedings of the 29th European Conference on Information Systems (ECIS), AIS. short: 'C. Vorbohle, S. Gottschalk, in: Proceedings of the 29th European Conference on Information Systems (ECIS), AIS, n.d.' conference: location: Virtual Conference/Workshop name: 29th European Conference on Information Systems (ECIS) date_created: 2021-04-23T13:38:54Z date_updated: 2022-01-06T06:55:12Z department: - _id: '66' - _id: '534' - _id: '276' keyword: - Platform Ecosystems - Platform Ecosystem Modeling Language - Platform Ecosystem Development Tool - Business Models - Design Science language: - iso: eng project: - _id: '1' name: SFB 901 - _id: '4' name: SFB 901 - Project Area C - _id: '17' name: SFB 901 - Subproject C5 publication: Proceedings of the 29th European Conference on Information Systems (ECIS) publication_status: accepted publisher: AIS status: public title: 'Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems ' type: conference user_id: '47208' year: '2021' ... --- _id: '20212' abstract: - lang: eng text: "Ideational impact refers to the uptake of a paper's ideas and concepts by subsequent research. It is defined in stark contrast to total citation impact, a measure predominantly used in research evaluation that assumes that all citations are equal. Understanding ideational impact is critical for evaluating research impact and understanding how scientific disciplines build a cumulative tradition. Research has only recently developed automated citation classification techniques to distinguish between different types of citations and generally does not emphasize the conceptual content of the citations and its ideational impact. To address this problem, we develop Deep Content-enriched Ideational Impact Classification (Deep-CENIC) as the first automated approach for ideational impact classification to support researchers' literature search practices. We evaluate Deep-CENIC on 1,256 papers citing 24 information systems review articles from the IT business value domain. We show that Deep-CENIC significantly outperforms state-of-the-art benchmark models. We contribute to information systems research by operationalizing the concept of ideational impact, designing a recommender system for academic papers based on deep learning techniques, and empirically exploring the ideational impact of the IT business value domain.\r\n" article_number: '113432' author: - first_name: Julian full_name: Prester, Julian last_name: Prester - first_name: Gerit full_name: Wagner, Gerit last_name: Wagner - first_name: Guido full_name: Schryen, Guido id: '72850' last_name: Schryen - first_name: Nik Rushdi full_name: Hassan, Nik Rushdi last_name: Hassan citation: ama: 'Prester J, Wagner G, Schryen G, Hassan NR. Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach. Decision Support Systems. 2021;140(January).' apa: 'Prester, J., Wagner, G., Schryen, G., & Hassan, N. R. (2021). Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach. Decision Support Systems, 140(January), Article 113432.' bibtex: '@article{Prester_Wagner_Schryen_Hassan_2021, title={Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach}, volume={140}, number={January113432}, journal={Decision Support Systems}, author={Prester, Julian and Wagner, Gerit and Schryen, Guido and Hassan, Nik Rushdi}, year={2021} }' chicago: 'Prester, Julian, Gerit Wagner, Guido Schryen, and Nik Rushdi Hassan. “Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach.” Decision Support Systems 140, no. January (2021).' ieee: 'J. Prester, G. Wagner, G. Schryen, and N. R. Hassan, “Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach,” Decision Support Systems, vol. 140, no. January, Art. no. 113432, 2021.' mla: 'Prester, Julian, et al. “Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach.” Decision Support Systems, vol. 140, no. January, 113432, 2021.' short: J. Prester, G. Wagner, G. Schryen, N.R. Hassan, Decision Support Systems 140 (2021). date_created: 2020-10-27T13:28:21Z date_updated: 2022-06-10T06:55:32Z ddc: - '000' department: - _id: '277' file: - access_level: open_access content_type: application/pdf creator: hsiemes date_created: 2020-10-27T13:31:01Z date_updated: 2020-10-27T13:31:01Z file_id: '20213' file_name: DECSUP-D-20-00312 - PREPUBLICATION.pdf file_size: 440903 relation: main_file file_date_updated: 2020-10-27T13:31:01Z has_accepted_license: '1' intvolume: ' 140' issue: January keyword: - Ideational impact - citation classification - academic recommender systems - natural language processing - deep learning - cumulative tradition language: - iso: eng oa: '1' publication: Decision Support Systems status: public title: 'Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach' type: journal_article user_id: '72850' volume: 140 year: '2021' ... --- _id: '31680' author: - first_name: Ingrid full_name: Scharlau, Ingrid id: '451' last_name: Scharlau orcid: 0000-0003-2364-9489 - first_name: A. full_name: Karsten, A. last_name: Karsten - first_name: Katharina J. full_name: Rohlfing, Katharina J. id: '50352' last_name: Rohlfing citation: ama: Scharlau I, Karsten A, Rohlfing KJ. Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing. Journal of Writing Research. 2021;12(vol. 12 issue 3):493-529. doi:10.17239/jowr-2021.12.03.01 apa: Scharlau, I., Karsten, A., & Rohlfing, K. J. (2021). Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing. Journal of Writing Research, 12(vol. 12 issue 3), 493–529. https://doi.org/10.17239/jowr-2021.12.03.01 bibtex: '@article{Scharlau_Karsten_Rohlfing_2021, title={Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing}, volume={12}, DOI={10.17239/jowr-2021.12.03.01}, number={vol. 12 issue 3}, journal={Journal of Writing Research}, publisher={ARLE (International Association for Research in L1 Education)}, author={Scharlau, Ingrid and Karsten, A. and Rohlfing, Katharina J.}, year={2021}, pages={493–529} }' chicago: 'Scharlau, Ingrid, A. Karsten, and Katharina J. Rohlfing. “Building, Emptying out, or Dreaming? Action Structures and Space in Students’ Metaphors of Academic Writing.” Journal of Writing Research 12, no. vol. 12 issue 3 (2021): 493–529. https://doi.org/10.17239/jowr-2021.12.03.01.' ieee: 'I. Scharlau, A. Karsten, and K. J. Rohlfing, “Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing,” Journal of Writing Research, vol. 12, no. vol. 12 issue 3, pp. 493–529, 2021, doi: 10.17239/jowr-2021.12.03.01.' mla: Scharlau, Ingrid, et al. “Building, Emptying out, or Dreaming? Action Structures and Space in Students’ Metaphors of Academic Writing.” Journal of Writing Research, vol. 12, no. vol. 12 issue 3, ARLE (International Association for Research in L1 Education), 2021, pp. 493–529, doi:10.17239/jowr-2021.12.03.01. short: I. Scharlau, A. Karsten, K.J. Rohlfing, Journal of Writing Research 12 (2021) 493–529. date_created: 2022-06-06T13:49:01Z date_updated: 2023-02-01T12:14:52Z department: - _id: '749' - _id: '424' doi: 10.17239/jowr-2021.12.03.01 intvolume: ' 12' issue: vol. 12 issue 3 keyword: - Literature and Literary Theory - Linguistics and Language - Language and Linguistics - Education language: - iso: eng page: 493-529 publication: Journal of Writing Research publication_identifier: issn: - 2030-1006 - 2294-3307 publication_status: published publisher: ARLE (International Association for Research in L1 Education) status: public title: Building, emptying out, or dreaming? Action structures and space in students’ metaphors of academic writing type: journal_article user_id: '14931' volume: 12 year: '2021' ... --- _id: '18686' author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Frederik Simon full_name: Bäumer, Frederik Simon id: '38837' last_name: Bäumer citation: ama: 'Kersting J, Bäumer FS. SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. In: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020. IADIS; 2020:119--123.' apa: 'Kersting, J., & Bäumer, F. S. (2020). SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123.' bibtex: '@inproceedings{Kersting_Bäumer_2020, title={SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH}, booktitle={PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020}, publisher={IADIS}, author={Kersting, Joschka and Bäumer, Frederik Simon}, year={2020}, pages={119--123} }' chicago: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, 119--123. IADIS, 2020.' ieee: 'J. Kersting and F. S. Bäumer, “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH,” in PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, Lisbon, Portugal, 2020, pp. 119--123.' mla: 'Kersting, Joschka, and Frederik Simon Bäumer. “SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH.” PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.' short: 'J. Kersting, F.S. Bäumer, in: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020, IADIS, 2020, pp. 119--123.' conference: end_date: 20.11.2020 location: Lisbon, Portugal name: 17th International Conference on Applied Computing start_date: 18.11.2020 date_created: 2020-08-31T10:59:54Z date_updated: 2022-01-06T06:53:51Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-11-19T17:29:03Z date_updated: 2020-11-19T17:29:03Z file_id: '20443' file_name: Kersting & Bäumer (2020), Kersting2020d.pdf file_size: 1064877 relation: main_file success: 1 file_date_updated: 2020-11-19T17:29:03Z has_accepted_license: '1' keyword: - Software Requirements - Natural Language Processing - Transfer Learning - On-The-Fly Computing language: - iso: eng page: 119--123 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 publication: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON APPLIED COMPUTING 2020 publisher: IADIS status: public title: 'SEMANTIC TAGGING OF REQUIREMENT DESCRIPTIONS: A TRANSFORMER-BASED APPROACH' type: conference user_id: '58701' year: '2020' ... --- _id: '15580' abstract: - lang: eng text: This paper deals with aspect phrase extraction and classification in sentiment analysis. We summarize current approaches and datasets from the domain of aspect-based sentiment analysis. This domain detects sentiments expressed for individual aspects in unstructured text data. So far, mainly commercial user reviews for products or services such as restaurants were investigated. We here present our dataset consisting of German physician reviews, a sensitive and linguistically complex field. Furthermore, we describe the annotation process of a dataset for supervised learning with neural networks. Moreover, we introduce our model for extracting and classifying aspect phrases in one step, which obtains an F1-score of 80%. By applying it to a more complex domain, our approach and results outperform previous approaches. author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 citation: ama: 'Kersting J, Geierhos M. Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020). Setúbal, Portugal: SCITEPRESS; 2020:391--400.' apa: 'Kersting, J., & Geierhos, M. (2020). Aspect Phrase Extraction in Sentiment Analysis with Deep Learning. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) (pp. 391--400). Setúbal, Portugal: SCITEPRESS.' bibtex: '@inproceedings{Kersting_Geierhos_2020, place={Setúbal, Portugal}, title={Aspect Phrase Extraction in Sentiment Analysis with Deep Learning}, booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020)}, publisher={SCITEPRESS}, author={Kersting, Joschka and Geierhos, Michaela}, year={2020}, pages={391--400} }' chicago: 'Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning.” In Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), 391--400. Setúbal, Portugal: SCITEPRESS, 2020.' ieee: J. Kersting and M. Geierhos, “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning,” in Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), Valetta, Malta, 2020, pp. 391--400. mla: Kersting, Joschka, and Michaela Geierhos. “Aspect Phrase Extraction in Sentiment Analysis with Deep Learning.” Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, 2020, pp. 391--400. short: 'J. Kersting, M. Geierhos, in: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) --  Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020), SCITEPRESS, Setúbal, Portugal, 2020, pp. 391--400.' conference: location: Valetta, Malta name: International Conference on Agents and Artificial Intelligence (ICAART) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI) date_created: 2020-01-15T08:35:07Z date_updated: 2022-01-06T06:52:29Z ddc: - '000' department: - _id: '579' file: - access_level: closed content_type: application/pdf creator: jkers date_created: 2020-09-18T09:27:00Z date_updated: 2020-09-18T09:27:00Z file_id: '19576' file_name: Kersting & Geierhos (2020), Kersting2020.pdf file_size: 421780 relation: main_file success: 1 file_date_updated: 2020-09-18T09:27:00Z has_accepted_license: '1' keyword: - Deep Learning - Natural Language Processing - Aspect-based Sentiment Analysis language: - iso: eng page: 391--400 place: Setúbal, Portugal project: - _id: '3' name: SFB 901 - Project Area B - _id: '1' name: SFB 901 - _id: '9' name: SFB 901 - Subproject B1 publication: Proceedings of the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) -- Special Session on Natural Language Processing in Artificial Intelligence (NLPinAI 2020) publisher: SCITEPRESS status: public title: Aspect Phrase Extraction in Sentiment Analysis with Deep Learning type: conference user_id: '58701' year: '2020' ... --- _id: '46149' abstract: - lang: eng text: 'The paper presents a cross-European survey on teachers and crowdsourcing. The survey examines how familiar language teachers are with the concept of crowdsourcing and addresses their attitude towards including crowdsourcing into language teaching activities. The survey was administrated via an online questionnaire and collected volunteers’ data on: (a) teachers’ experience with organizing crowdsourcing activities for students/pupils, (b) the development of crowdsourced resources and materials as well as (c) teachers’ motivation for participating in or employing crowdsourcing activities. The questionnaire was disseminated in over 30 European countries. The final sample comprises 1129 language teachers aged 20 to 65, mostly working at institutions of tertiary education. The data indicates that many participants are not familiar with the concept of crowdsourcing resulting in a low rate of crowdsourcing activities in the classroom. However, a high percentage of responding teachers is potentially willing to crowdsource teaching materials for the language(s) they teach. They are particularly willing to collaborate with other teachers in the creation of interactive digital learning materials, and to select, edit, and share language examples for exercises or tests. Since the inclusion of crowdsourcing activities in language teaching is still in its initial stage, steps for further research are highlighted.' alternative_title: - Insights from a Cross-European Survey author: - first_name: Špela full_name: Arhar Holdt, Špela last_name: Arhar Holdt - first_name: Lorenzo full_name: Zanasi, Lorenzo last_name: Zanasi - first_name: Tassja full_name: Weber, Tassja id: '89571' last_name: Weber - first_name: Elena full_name: Volodina, Elena last_name: Volodina - first_name: Christos full_name: Rodosthenous, Christos last_name: Rodosthenous - first_name: Antonia full_name: Ordulj, Antonia last_name: Ordulj - first_name: Lina full_name: Miloshevska, Lina last_name: Miloshevska - first_name: Ivana full_name: Lazić Konjik, Ivana last_name: Lazić Konjik - first_name: Svetla full_name: Koeva, Svetla last_name: Koeva - first_name: Ramunė full_name: Kasperavičienė, Ramunė last_name: Kasperavičienė - first_name: Ciler full_name: Hatipoglu, Ciler last_name: Hatipoglu - first_name: Karën full_name: Fort, Karën last_name: Fort - first_name: Petra full_name: Bago, Petra last_name: Bago - first_name: Isabel full_name: Durán-Muñoz, Isabel last_name: Durán-Muñoz - first_name: Elżbieta full_name: Gajek, Elżbieta last_name: Gajek - first_name: Rina full_name: Zviel-Girshin, Rina last_name: Zviel-Girshin citation: ama: Arhar Holdt Š, Zanasi L, Weber T, et al. Language Teachers and Crowdsourcing. Rasprave Instituta za hrvatski jezik i jezikoslovlje. 2020;46(1):1-28. doi:10.31724/rihjj.46.1.1 apa: Arhar Holdt, Š., Zanasi, L., Weber, T., Volodina, E., Rodosthenous, C., Ordulj, A., Miloshevska, L., Lazić Konjik, I., Koeva, S., Kasperavičienė, R., Hatipoglu, C., Fort, K., Bago, P., Durán-Muñoz, I., Gajek, E., & Zviel-Girshin, R. (2020). Language Teachers and Crowdsourcing. Rasprave Instituta Za Hrvatski Jezik i Jezikoslovlje, 46(1), 1–28. https://doi.org/10.31724/rihjj.46.1.1 bibtex: '@article{Arhar Holdt_Zanasi_Weber_Volodina_Rodosthenous_Ordulj_Miloshevska_Lazić Konjik_Koeva_Kasperavičienė_et al._2020, title={Language Teachers and Crowdsourcing}, volume={46}, DOI={10.31724/rihjj.46.1.1}, number={1}, journal={Rasprave Instituta za hrvatski jezik i jezikoslovlje}, publisher={Institute of Croatian Language and Linguistics}, author={Arhar Holdt, Špela and Zanasi, Lorenzo and Weber, Tassja and Volodina, Elena and Rodosthenous, Christos and Ordulj, Antonia and Miloshevska, Lina and Lazić Konjik, Ivana and Koeva, Svetla and Kasperavičienė, Ramunė and et al.}, year={2020}, pages={1–28} }' chicago: 'Arhar Holdt, Špela, Lorenzo Zanasi, Tassja Weber, Elena Volodina, Christos Rodosthenous, Antonia Ordulj, Lina Miloshevska, et al. “Language Teachers and Crowdsourcing.” Rasprave Instituta Za Hrvatski Jezik i Jezikoslovlje 46, no. 1 (2020): 1–28. https://doi.org/10.31724/rihjj.46.1.1.' ieee: 'Š. Arhar Holdt et al., “Language Teachers and Crowdsourcing,” Rasprave Instituta za hrvatski jezik i jezikoslovlje, vol. 46, no. 1, pp. 1–28, 2020, doi: 10.31724/rihjj.46.1.1.' mla: Arhar Holdt, Špela, et al. “Language Teachers and Crowdsourcing.” Rasprave Instituta Za Hrvatski Jezik i Jezikoslovlje, vol. 46, no. 1, Institute of Croatian Language and Linguistics, 2020, pp. 1–28, doi:10.31724/rihjj.46.1.1. short: Š. Arhar Holdt, L. Zanasi, T. Weber, E. Volodina, C. Rodosthenous, A. Ordulj, L. Miloshevska, I. Lazić Konjik, S. Koeva, R. Kasperavičienė, C. Hatipoglu, K. Fort, P. Bago, I. Durán-Muñoz, E. Gajek, R. Zviel-Girshin, Rasprave Instituta Za Hrvatski Jezik i Jezikoslovlje 46 (2020) 1–28. date_created: 2023-07-26T07:05:01Z date_updated: 2023-07-26T07:43:38Z doi: 10.31724/rihjj.46.1.1 extern: '1' intvolume: ' 46' issue: '1' keyword: - Linguistics and Language - Language and Linguistics language: - iso: eng page: 1-28 publication: Rasprave Instituta za hrvatski jezik i jezikoslovlje publication_identifier: issn: - 1849-0379 - 1331-6745 publication_status: published publisher: Institute of Croatian Language and Linguistics status: public title: Language Teachers and Crowdsourcing type: journal_article user_id: '89571' volume: 46 year: '2020' ...