A rejection system, also referred to as a complementary calculus, is a proof system axiomatising the invalid formulas of a logic, in contrast to traditional calculi which axiomatise the valid ones. Rejection systems t...
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Taxonomy mining plays an important role for organizing and structuring of data in Content managementsystems (CMS). In this paper, we propose a novel approach that leverages multidimensional knowledge representation (...
Taxonomy mining plays an important role for organizing and structuring of data in Content managementsystems (CMS). In this paper, we propose a novel approach that leverages multidimensional knowledge representation (MKR) for taxonomy mining from text documents and enriching the extracted information via Large Language Model (LLM). The data originates from a Smart City project in Germany, which addresses housing, care and health for elderly people. The applied method involves the extraction of relevant keywords from text and the utilization of the MKR framework to analyze and represent the information. Results are provided for a context builder that utilizes GPT-4 to enrich the taxonomy. The enriched taxonomy is then used in a WordPress CMS for information search, structuring and tagging of the blog entries accordingly.
This short paper describes an exemplary Smart City model-project called LOKAL-digital. The model area is the city of Netphen in Germany, a city located in a rural area of North Rhine- Westphalia of about 23.000 inhabi...
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This paper presents a knowledge graph-informed smart UX-design approach for supporting information retrieval for a wearable, providing treatment recommendations during emergency situations to health professionals. Thi...
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Society 5.0 is the logical further development of what has emerged in Germany under Industry 4.0. The concept proposed by Japanese is being applied to society. The effects on the world of work and social life are very...
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In the era of personalized education, the provision of comprehensible explanations for learning recommendations is of great value to enhance the learner's understanding and engagement with the recommended learning...
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ISBN:
(数字)9798350394023
ISBN:
(纸本)9798350394030
In the era of personalized education, the provision of comprehensible explanations for learning recommendations is of great value to enhance the learner's understanding and engagement with the recommended learning content. Large language models (LLMs) and generative AI have recently opened new doors for generating human-like explanations, for and along learning recommendations. However, their precision is still far away from acceptable in a sensitive field like education. To harness the abilities of LLMs, while still ensuring a high level of precision towards the intent of the learners, this paper proposes an approach to utilize knowledge graphs (KG) as a source of factual context for LLM prompts, reducing the risk of model hallucinations, and safeguarding against wrong or imprecise information, while maintaining an application-intended learning context. We utilize the semantic relations in the knowledge graph to offer curated knowledge about learning recommendations. With domain-experts in the loop, we design the explanation as a textual template, which is filled and completed by the LLM. Domain experts were integrated in the prompt engineering phase as part of a study, to ensure that explanations include information that is relevant to the learner. We evaluate our approach quantitatively using Rouge-N and Rouge-L measures, as well as qualitatively with experts and learners. Our results show an enhanced recall and precision of the generated explanations compared to those generated solely by the GPT model, with a greatly reduced risk of generating imprecise information in the final learning explanation.
This paper investigates the learning capability and adaptability of a digital consulting assistant in the WordPress Content management System (CMS). The assistant is used in the Smart City context for advice and infor...
This paper investigates the learning capability and adaptability of a digital consulting assistant in the WordPress Content management System (CMS). The assistant is used in the Smart City context for advice and information in the areas of care, housing and digitalization. The results originated from the LOKAL-digital project, a digitalization project at the municipal level in the city of Netphen, which is located in the rural area of the district of Siegen-Wittgenstein, Germany. The aim of this research was to analyze the opportunities and challenges of integrating consulting assistants in content managementsystems and to investigate technical possibilities, e.g. via plugins, to continuously adapt to the needs of the users. By combining methods from artificial intelligence, personalized recommendations and contextual feedback, the goal is to create an optimal assistance experience for users.
Metadata play an important role in the organization of information. As data about data, they explain how information relates to one another, in what chronological sequence it arises, or what hierarchical structures ca...
Metadata play an important role in the organization of information. As data about data, they explain how information relates to one another, in what chronological sequence it arises, or what hierarchical structures can be formed. In the content management system of the smart city project “LOKAL-digital”, metadata is utilized for the structuring of information in the areas of housing, health and care. This paper gives practical approaches for the implementation of metadata management in the development of the information portal and reports on the lessons learned in building the knowledgemanagement solution. The use of metadata for structuring and searching content is discussed in various use cases.
Visual servoing is a well-established technique for object grasping and controls the robot in a closed-loop fashion. It typically uses hand-crafted features or a neural network that directly learns the control output....
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In the field of medicine and healthcare, the utilization of medical expertise, based on medical knowledge combined with patients’ health information is a life-critical challenge for patients and health professionals....
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ISBN:
(数字)9798350363012
ISBN:
(纸本)9798350363029
In the field of medicine and healthcare, the utilization of medical expertise, based on medical knowledge combined with patients’ health information is a life-critical challenge for patients and health professionals. The within-laying complexity and variety form the need for a united approach to gather, analyze, and utilize existing knowledge of medical treatments, and medical operations to provide the ability to present knowledge for the means of accurate patient-driven decision-making. One way to achieve this is the fusion of multiple knowledge sources in healthcare. It provides health professionals the opportunity to select from multiple contextual aligned knowledge sources which enables the support for critical decisions. This paper presents multiple conceptual models for knowledge fusion in the field of medicine, based on a knowledge graph structure. It will evaluate, how knowledge fusion can be enabled and presents how to integrate various knowledge sources into the knowledge graph for rescue operations.
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