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Reliable and Content-specific Support for Keyword Selection through AI and Statistics Characterising Educational Content with Large Language Models & Agreement Analyses

Reliable and Content-specific Support for Keyword Selection ...

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作者： Strube, Tom Nowak, Tom Pokotylo, Mariia Kuhlenkötter, Bernd Fraunhofer Institute for Software and Systems Engineering Dortmund Germany Ruhr University Bochum Bochum Germany

Due to the recent popularity and availability of Large Language Models (LLMs), creators of educational materials can more efficiently extract keywords for use in personalised learning recommendations than ever before. However, due to the LLMs' probabalistic nature, the automation of the otherwise labour-intense keyword extraction inherits the risk of biased and non-explainable results. In this research, we present an original framework to enhance keyword selection based on content title and description through a novel, reliability-sensitive, keyword selection algorithm. For this, we collected 38 potential keywords (together with their definitions) for five topics on dementia care from previous studies, together with two contents per topic. To assess the new method's support in extracting keywords, we then prompted 5 human experts and 3 LLMs (using Retrieval Augmented Generation (RAG) for the keyword definitions) to select keywords to include and exclude for each content. Using Krippendorf's a metric, we then were able to adapt to the present agreement, and to reliably select keyword sets for inclusion and exclusion for each content individually. Last, we compared these LLM-based keyword sets with those selected by humans to assess the impact of the adaptive keyword selection algorithm. Overall, the results suggest that LLMs generally struggle with the task (66% of extraction attempts either contained hallucinated or did not return any keywords), and topic-wise internal agreement is low (a=0.59 (0.42) for model 3 (using RAG) on average;α=0.68 for human raters). Due to this, the reliable keyword selection resulted in a median set of 6|27 keywords for inclusion|exclusion per topic, with many of those keywords being within the benchmark keyword sets selected by human raters. To conclude, this approach shows effective in adapting to different levels of agreement in extracting keywords. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Reliability analysis

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Supporting Changes in Digital Ownership and Data Sovereignty Across the Automotive Value Chain with Catena-X

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Procedia Computer Science 2025年 253卷 374-383页

作者： Marvin Manoury Theresa Riedelsheimer Malte Hellmeier Tom Meyer Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstrasse 8-9 10587 Berlin Germany Fraunhofer Institute for Software and Systems Engineering ISST Speicherstraße 6 44147 Dortmund Germany

Considering the concept of a Circular Economy, which entails several life cycles of, e.g., vehicles, their components, and materials, it is important to investigate how the respective Digital Twins are managed over the lifecycle of their physical assets. This publication presents and compares three approaches for managing Digital Twins in industrial use cases. For the aggregation of these approaches, a user-centered design approach has been used in the research project Catena-X which focuses on the automotive industry. The results are analyzed qualitatively based on aspects such as data ownership and data sovereignty. It was identified, that all three approaches have limitations and benefits which make them useful in different scenarios. An overview of their strengths and weaknesses is presented to select an appropriate approach In similar setups. The results described in this publication can be used to select the best update approach in data spaces where multiple stakeholders are able to update information on a single asset.

关键词： Digital Twins Ownership Circular Economy Data Sovereignty Supply Chain Catena-X

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Data Trading and Monetization: Challenges and Open Research Directions 7

Data Trading and Monetization: Challenges and Open Research ...

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7th International Conference on Future Networks and Distributed systems, ICFNDS 2023

作者： Ramadan, Qusai Boukhers, Zeyd Alshaikh, Muath Lange, Christoph Jurjens, Jan Institute Of Software Engineering University Of Koblenz Germany Fraunhofer Institute For Applied Information Technology Fit Germany Uniklinik Köln Germany College Of Computing And Informatics Saudi Electronic University Saudi Arabia Rwth Aachen University Germany University Of Koblenz Germany Fraunhofer-Institute For Software And Systems Engineering Isst Germany

ISBN: (纸本)9798400709036

Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking. © 2023 Owner/Author.

关键词： Electronic data interchange

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Pattern-based Requirements Elicitation for Sovereign Data Sharing

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Procedia Computer Science 2025年 254卷 147-156页

作者： Julia Pampus Maritta Heisel Fraunhofer Institute for Software and Systems Engineering ISST Speicherstraβe 6 44147 Dortmund Germany University of Duisburg-Essen Bismarckstr 90 47057 Duisburg Germany

The growing data economy increasingly focuses on self-determined and autonomous data sharing, supported by infrastructures that create a trustful and secure environment. A key feature in this context is the offering, negotiation, and enforcement of so-called data usage conditions (DUCs), also known as policies. The design of involved software systems requires a structured and stakeholder-specific elicitation of technical requirements. To address this issue, we define a requirements model, consisting of actor, dataset, and condition entities, for sovereign data sharing and present a method for requirements elicitation in form of a five-step agenda with 13 validation conditions (VCs). The application of this method produces a set of instantiated requirements templates that provide descriptive information about involved actors, identified datasets, and applied DUCs. We demonstrate our method using an established use case from the automotive industry and evaluate it in qualitative expert interviews.

关键词： Data Sharing Sovereignty Data Usage Conditions Data Spaces Patterns Requirements engineering

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Data sovereignty needs in agricultural use cases 43

Data sovereignty needs in agricultural use cases

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43. Jahrestagung der Gesellschaft fur Informatik in der Land-, Forst- und Ernahrungswirtschaft - Resiliente Agri-Food-Systeme: Herausforderungen und Losungsansatze, GIL 2023 - 43rd Annual Conference of the Society for Informatics in Agriculture, Forestry, and Food Industry - Resilient Agri-Food systems: Challenges and Solutions, GIL 2023

作者： Boye, Fredrik Matar, Raghad Neuschwander, Philipp Fraunhofer IVI Fraunhofer Institute for Transportation and Infrastructure Systems Dresden01069 Germany Fraunhofer IESE Fraunhofer Institute for Experimental Software Engineering Kaiserslautern67663 Germany

ISBN: (纸本)9783885797241

With today's shift towards digital farming, data transfer and processing are becoming increasingly essential for optimizing farm operations. In the complex arable farming sector, there exist numerous use cases involving a variety of actors and processes. Designing new digital ecosystems, such as agricultural data spaces that support existing workflows while enabling new opportunities for data-driven services, requires a good understanding of existing processes and data sovereignty needs. In this paper, we categorize data exchange use cases in arable farming and analyze the respective data sovereignty needs for each category. The results of our contribution can be used as a basis for further analysis and evaluation of data-sharing approaches in terms of their suitability for meeting different data sovereignty needs in agriculture, as well as in the process of requirements analysis when designing such systems. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Electronic data interchange

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SUPPORTING CHANGES IN DIGITAL OWNERSHIP AND DATA SOVEREIGNTY ACROSS THE AUTOMOTIVE VALUE CHAIN WITH CATENA-X

arXiv

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arXiv 2024年

作者： Manoury, Marvin Riedelsheimer, Theresa Hellmeier, Malte Meyer, Tom Fraunhofer Institute for Production Systems and Design Technology IPK Pascalstrasse 8-9 Berlin10587 Germany Fraunhofer Institute for Software and Systems Engineering ISST Speicherstraße 6 Dortmund44147 Germany

Digital Twins have evolved as a concept describing digital representations of physical assets. They can be used to facilitate simulations, monitoring, or optimization of product lifecycles. Considering the concept of a Circular Economy, which entails several lifecycles of, e.g., vehicles, their components, and materials, it is important to investigate how the respective Digital Twins are managed over the lifecycle of their physical assets. This publication presents and compares three approaches for managing Digital Twins in industrial use cases. The analysis considers aspects such as updates, data ownership, and data sovereignty. The results based on the research project Catena-X © 2024, CC BY-NC-ND.

关键词： Supply chains

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eDEM-CONNECT: An Ontology-Based Chatbot for Family Caregivers of People with Dementia 12th

eDEM-CONNECT: An Ontology-Based Chatbot for Family Caregive...

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12th International Conference on Mobile Communication and Healthcare, MobiHealth 2023

作者： Boiting, Maurice Tschorn, Niklas Suravee, Sumaiya Yordanova, Kristina Halek, Margareta Jagoda, Franziska A. Lüdtke, Stefan Burmann, Anja Fraunhofer Institute for Software and Systems Engineering ISST Dortmund44147 Germany Institute for Data Science Universität Greifswald Greifswald17489 Germany School of Nursing Science Faculty of Health Universiät Witten/Herdecke Witten58453 Germany Institute for Visual and Analytic Computing Universät Rostock Rostock18059 Germany

ISBN: (纸本)9783031606649

Home care of people with dementia (PwD) is mainly organized and carried out by non-professional family caregivers, who struggle to interpret the needs of PwD correctly and are confronted with the challenging behavior of their relatives. Although support services for family caregivers are widespread in Germany, they are rarely used due to the fact that information is poorly organized and relatives are faced with a flood of disorganized, outdated, and confusing content. Due to the technical development of chatbot technologies (ChatGPT), chatbots gain more and more relevance. Based on the new technological possibilities, we developed an online communication and service platform with an integrated chatbot within the eDEM-CONNECT project, with the aim of making structured and easily understandable information accessible for family caregivers. This work focuses on the development of a chatbot pipeline that has broad domain knowledge through a provided ontology on the topic of agitation of PwD. This allows the chatbot to provide relevant and peer-reviewed information to family members. In our approach, a patient history is first taken based on several diagnostic questions so that relevant information can be output in a later step. For this purpose, we demonstrate that agitations in natural language can be correctly recognized by the used BERT model and that our developed chatbot is able to select further diagnostic questions based on the predictions of a Markov logic network. © ICST institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Neurodegenerative diseases

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Potentials and Barriers of the Metaverse for Circular Economy

Potentials and Barriers of the Metaverse for Circular Econom...

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Simulation Winter Conference

作者： Julia Kunert Hendrik van der Valk Hannah Scheerer Christoph Hoppe Chair for Industrial Inform. Management TU Dortmund University Dortmund NRW Germany Fraunhofer Institute for Software and Systems Engineering ISST Dortmund NRW Germany Dept. of Industrial Manufacturing Fraunhofer ISST Dortmund NRW Germany

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Sustainability is a challenge for society that circular economy tries to tackle. The metaverse, as an emerging technology that incorporates digital twins and simulation in an immersive virtual environment, has not been thoroughly investigated in connection to circular economy. Thus, the purpose of this study is to summarize the potentials and barriers of the use of the metaverse for circular economy. By conducting a structured literature review, this paper categorizes the findings into dimensions that are important for both the metaverse and circular economy. A variety of potentials and barriers that cover different perspectives important for businesses aiming to comply with circular economy principles is discovered. The findings include potentials and barriers in several areas, like the access to the metaverse, connected costs, data, knowledge transfer, collaboration, innovation, product design, production planning, training of employees, and transportation. The results can be used to promote the implementation of circular economy principles.

关键词： Training Technological innovation Costs Metaverse Transportation Collaboration Product design Sustainable development Business Systematic literature review

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Integrating Scheduling of Logistic Support Processes in Agent-Based Industry 4.0 Assembly Simulation 23

Integrating Scheduling of Logistic Support Processes in Agen...

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Proceedings of the Winter Simulation Conference

作者： Adrian Freiter Christian Schwede Department of Logistics Fraunhofer Institute for Software and Systems Engineering (ISST) Dortmund GERMANY Faculty of Engineering and Mathematics University of Applied Sciences and Arts Bielefeld Bielefeld GERMANY

ISBN: (纸本)9798350369663

The upcoming decentralized production systems seem to be promising in Industry 4.0 assembly to handle the challenges of highly individual products. Matrix production characterized by freely linked workstations and an advanced automation level are highly flexible. That is why many efforts have already been made to explore the advantages compared to existing flow shop production systems, but also the additional challenges arising from this new paradigm. One of these challenges is the synchronization of main product and supply part flow at the individual workstations during order scheduling. This paper presents a new approach of integrating logistics support processes into the scheduling of the main product flow to consider the part supply in the decisions taken during scheduling avoiding waiting times. We compare our integrated approach with the existing decoupled scheduling approach, based on a "bicycle assembly" scenario. The results are promising particularly when part supply is a bottleneck.

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GAN-Based Data Augmentation for Improving Biometric Authentication Using CWT Images of Blood Flow Sounds

GAN-Based Data Augmentation for Improving Biometric Authenti...

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17th International Joint Conference on Biomedical engineering systems and Technologies, BIOSTEC 2024

作者： Sahare, Natasha Fuentealba, Patricio Salvi, Rutuja Burmann, Anja Henze, Jasmin Fraunhofer Institute for Software and Systems Engineering ISST Dortmund Germany Technical University of Dortmund Dortmund Germany Instituto de Electricidad y Electrónica Facultad de Ciencias de la Ingeniería Universidad Austral de Chile Valdivia Chile IDTM GmbH Recklinghausen Germany

Biometric identification allows to secure sensitive information. Since existing biometric traits, such as finger prings, voice, etc. are associated with different limitations, we exemplified the potential of blood flow sounds for biometric authentication in previous work. Therefore, we used measurements from seven different users acquired with a custom-built auscultation device to calculate the spectrograms of these signals for each cardiac cycle using continuous wavelet transform (CWT). The resulting spectral images were then used for training of a convolutional neural network (CNN). In this work, we repeated the same experiment with data from twelve users by adding more data from the original seven users and data from five more users. This lead to an imbalanced dataset, where the amount of available data for the new users was much smaller, e.g., U1 had more than 900 samples per side whereas the new user U9 had less than 100 samples per side. We experienced a lower performance for the new users, i.e. their sensitivity was 18-21% lower than the overall accuracy. Thus, we examined whether the augmentation of data leads to better results. This analysis was performed using generative adversarial networks (GANs). The newly generated data was then used for training of a CNN with several different settings, revealing the potential of GAN-based data augmentation for increasing the accuracy of biometric authentication using blood flow sounds. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Generative adversarial networks

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