A5053761025- Semantic Web and Ontologies
- Natural Language Processing Techniques
- Topic Modeling
- Advanced Graph Neural Networks
- Data Quality and Management
- Scientific Computing and Data Management
- Biomedical Text Mining and Ontologies
- Data Mining Algorithms and Applications
- Antenna Design and Optimization
- Antenna Design and Analysis
- Advanced MIMO Systems Optimization
- Research Data Management Practices
- Wikis in Education and Collaboration
- Graph Theory and Algorithms
- Distributed and Parallel Computing Systems
- Distributed systems and fault tolerance
- Service-Oriented Architecture and Web Services
- Text Readability and Simplification
- Privacy-Preserving Technologies in Data
- Advanced Data Storage Technologies
- Educational Technology and Assessment
- Web Data Mining and Analysis
- Advanced Database Systems and Queries
- Digital Transformation in Industry
Leipzig University
2018-2024
Institut für Angewandte Trainingswissenschaft
2024
Institut für Biomedizinische Analytik und NMR Imaging (Germany)
2023
Karlsruhe Institute of Technology
2017
Heterogeneous data, different definitions and incompatible models are a huge problem in many domains, with no exception for the field of energy systems analysis. Hence, it is hard to re-use results, compare model results or couple at all. Ontologies provide precisely defined vocabulary build common shared conceptualisation domain. Here, we present Open Energy Ontology (OEO) developed domain Using OEO provides several benefits community. First, enables consistent annotation large amounts data...
The maintenance and use of metadata such as provenance time-related information is increasing importance in the Semantic Web, especially for Big Data applications that work on heterogeneous data from multiple sources which require high quality. In an RDF dataset, it possible to s tore alongside actual several representation models have been proposed. However, there still no in-depth comparative evaluation main alternatives both conceptual level implementation using different graph backends....
Although many FAIR principles could be fulfilled by 5-star Linked Open Data, the successful realization of poses a multitude challenges. publishing and retrieval Data is still rather FAIRytale than reality, for users machines. In this paper, we give an overview on four major approaches that tackle individual challenges data present our vision backbone. We propose 1) DBpedia Databus - flexible, heavily automatable dataset management platform based DataID metadata; extended 2) novel Mods...
This paper examines the current landscape of ontologies for describing additive manufacturing (AM) technologies and services. Through an extensive search, using both a bottom-up top-down approach, four accessible AM were identified. These then evaluated according to generally accepted principles guidelines. It was found, that two could deal as starting point semantic core B2B services matchmaking platform. To remedy existing problems impracticability, underdevelopment, lacking linkage other...
In this work we will show that language models with less than one billion parameters can be used to translate natural SPARQL queries after fine-tuning. Using three different datasets ranging from academic real world, identify prerequisites the training data must fulfill in order for successful. The goal is empower users of semantic web technology use AI assistance affordable commodity hardware, making them more resilient against external factors.
The integration of Large Language Models (LLMs) with Knowledge Graphs (KGs) offers significant synergistic potential for knowledge-driven applications. One possible is the interpretation and generation formal languages, such as those used in Semantic Web, SPARQL being a core technology accessing KGs. In this paper, we focus on measuring out-of-the box capabilities LLMs to work more specifically SELECT queries applying quantitative approach. We implemented various benchmarking tasks...
Knowledge Graphs (KG) provide us with a structured, flexible, transparent, cross-system, and collaborative way of organizing our knowledge data across various domains in society industrial as well scientific disciplines. KGs surpass any other form representation terms effectiveness. However, Graph Engineering (KGE) requires in-depth experiences graph structures, web technologies, existing models vocabularies, rule sets, logic, best practices. It also demands significant amount work....
The amount, size, complexity, and importance of Knowledge Graphs (KGs) have increased during the last decade. Many different communities chosen to publish their datasets using Linked Data principles, which favors integration this information with many other sources published same principles technologies. Such a scenario requires develop techniques Summarization. concept class is one core elements used define ontologies sustain most existing KGs. Moreover, classes are an excellent tool refer...
In this paper multiple input output (MIMO) channel samples are generated by the use of a simple model that allows for arbitrary selection propagation paths. The distributions direction departure (DOD), arrival (DOA) and phases amplitudes can be selected each path. antenna array geometry element radiation patterns also included chosen arbitrarily. An synthesis method is based on eigenbeamforming then applied to simulated channels. It optimal solution considered problem maximizes ergodic...
As the field of Large Language Models (LLMs) evolves at an accelerated pace, critical need to assess and monitor their performance emerges. We introduce a benchmarking framework focused on knowledge graph engineering (KGE) accompanied by three challenges addressing syntax error correction, facts extraction dataset generation. show that while being useful tool, LLMs are yet unfit assist in generation with zero-shot prompting. Consequently, our LLM-KG-Bench provides automatic evaluation...
Large Language Models (LLMs) are advancing at a rapid pace, with significant improvements natural language processing and coding tasks. Yet, their ability to work formal languages representing data, specifically within the realm of knowledge graph engineering, remains under-investigated. To evaluate proficiency various LLMs, we created set five tasks that probe parse, understand, analyze, create graphs serialized in Turtle syntax. These tasks, each embodying distinct degrees complexity being...