@inproceedings{7068,
  abstract     = {Adopting digital twin technologies in small andmedium-sized enterprises (SMEs) is often hinderedby heterogeneous, poorly documented productiondata. Current semantic type detection approachesrequire massive labeled datasets making themimpractical for resource-constrained SMEs. Wepropose a zero-shot hybrid framework combiningpattern-based classification with selective largelanguage model (LLM) reasoning formanufacturing-specific data types. The two-stagearchitecture uses rule-based patterns for high-confidence cases, forwarding ambiguous columnsto a multi-step LLM reasoner. Evaluation on fourmanufacturing datasets shows the hybrid approachachieves weighted F1 within 7 24 percentagepoints of pure LLM classification performancewhile reducing LLM invocations by 39% onaverage. Processing time decreased by up to 2.8×.Our framework addresses a critical gap: automated,computationally efficient data type recognition formanufacturing SMEs without requiring trainingdata, contributing to automated simulation anddigital twin construction.},
  author       = {Döring, Lina and Trojahn, Sebastian and Reusch, Pascal},
  booktitle    = {19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management},
  editor       = {Behrendt, Fabian and Zadek, Hartmut and Janmontree, Jettarat and Trojahn, Sebastian and Lang, Sebastian},
  keywords     = {Semantic Data Type Detection, DigitalTwin, Manufacturing SMEs, Zero-shot Learning, Hybrid AI, LLM},
  location     = {Magdeburg},
  publisher    = {Otto von Guericke University Library, Magdeburg, Germany},
  title        = {{Smart data adapter: A hybrid pattern-LLM approach}},
  doi          = {10.25673/123544},
  year         = {2026},
}

@article{6244,
  author       = {Niederhaus, Marvin and Migenda, Nico and Weller, Julian and Kohlhase, Martin and Schenck, Wolfram},
  issn         = {2504-2289},
  journal      = {Big Data and Cognitive Computing},
  keywords     = {prescriptive analytics, prescriptive platforms, advanced data analytics, retrieval-augmented generation, graph-based retrieval-augmented generation, large language models, generative AI, genAI, recommender system},
  number       = {10},
  publisher    = {MDPI AG},
  title        = {{Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems}},
  doi          = {10.3390/bdcc9100261},
  volume       = {9},
  year         = {2025},
}

@inproceedings{6352,
  author       = {Kampe, Tim and Haas, Christian},
  booktitle    = {International Entrepreneurship Education Summit (IEES), Hochschule der Medien, Stuttgart, 28.11. },
  keywords     = {Professional Service Firm, Business Model Canvas, AI, Accounting Firm, Law Firm, Executive Search, Consulting Firm},
  location     = {Stuttgart},
  title        = {{The Impact of Digitalization and Artificial Intelligence on Professional Service Firms and their Business Models: The Good, the Bad, and the Ugly}},
  year         = {2025},
}

@inproceedings{6175,
  author       = {Halbrügge, Marc and Jungeblut, Thorsten},
  booktitle    = {KogWis 2025. 16th Biannual Conference of the German Cognitive Science Society.},
  keywords     = {Explainable AI, XAI, LIME},
  location     = {Bochum},
  title        = {{Beyond Heatmaps: Evaluating LIME Visualizations for Human Understandability}},
  year         = {2025},
}

@article{4881,
  author       = {Wiegraebe, Frauke and Schönbeck, Marleen and Wunderlich, Paul and Nauerth, Annette and Dörksen, Helene},
  issn         = {1430-9653},
  journal      = {Pflege und Gesellschaft},
  keywords     = {Digital care support tool, caring workforce, interdisciplinarity, AI application, machine learning, user orientation},
  pages        = {271--285},
  publisher    = {BeltzJuventa},
  title        = {{KI-basiertes Unterstützungstool für pflegende Erwerbstätige}},
  doi          = {10.3262/P&G2403271},
  volume       = {3},
  year         = {2024},
}

@article{3505,
  author       = {Süße, Thomas and Kobert, Maria and Kries, Caroline},
  issn         = {2325-5676},
  journal      = {Labour and Industry},
  keywords     = {Human-AI interaction, AI competence, AI-based agents, transformation of work},
  pages        = {1--20},
  publisher    = {Informa UK Limited},
  title        = {{Human-AI interaction in remanufacturing: exploring shop floor workers’ behavioural patterns within a specific human-AI system}},
  doi          = {10.1080/10301763.2023.2251103},
  year         = {2023},
}

@article{4482,
  author       = {Baudisch, Justin and Richter, Birte and Jungeblut, Thorsten},
  issn         = {1610-1987},
  journal      = {KI - Künstliche Intelligenz},
  keywords     = {Ambient assisted living, anomaly detection, Internet of Things, Explainable AI},
  number       = {3-4},
  pages        = {259--266},
  publisher    = {Springer Science and Business Media LLC},
  title        = {{A Framework for Learning Event Sequences and Explaining Detected Anomalies in a Smart Home Environment}},
  doi          = {10.1007/s13218-022-00775-5},
  volume       = {36},
  year         = {2022},
}