A5102785999- Semantic Web and Ontologies
- Advanced Graph Neural Networks
- Topic Modeling
- Data Quality and Management
- Biomedical Text Mining and Ontologies
- Scientific Computing and Data Management
- Advanced Database Systems and Queries
- Research Data Management Practices
- Library Science and Information Systems
- Web Data Mining and Analysis
- Bayesian Modeling and Causal Inference
- Natural Language Processing Techniques
- Complex Network Analysis Techniques
- Big Data and Business Intelligence
- Graph Theory and Algorithms
- Bioinformatics and Genomic Networks
- Data Mining Algorithms and Applications
- scientometrics and bibliometrics research
- Open Education and E-Learning
- Online Learning and Analytics
- Wikis in Education and Collaboration
- Neural Networks and Applications
- Machine Learning in Healthcare
- Advanced Text Analysis Techniques
- Artificial Intelligence in Healthcare and Education
Institute of Computer Vision and Applied Computer Sciences
2024
Institut für Biomedizinische Analytik und NMR Imaging (Germany)
2020-2024
TU Dresden
2024
Technische Informationsbibliothek (TIB)
2024
University of Oxford
2019-2022
University of Bonn
2014-2021
Subspace distance is an invaluable tool exploited in a wide range of feature selection methods. The power subspace that it can identify representative subspace, including group features efficiently approximate the space original features. On other hand, employing intrinsic statistical information data play significant role process. Nevertheless, most existing methods founded on are limited properly fulfilling this objective. To pursue void, we propose framework takes into account which...
Performing link prediction using knowledge graph embedding models has become a popular approach for completion. Such employ transformation function that maps nodes via edges into vector space in order to measure the likelihood of links. While mapping individual nodes, structure subgraphs is also transformed. Most designed Euclidean geometry usually support single type -- often translation or rotation, which suitable learning on graphs with small differences neighboring subgraphs. However,...
Skilled employees are the most important pillars of an organization. Despite this, organizations face high attrition and turnover rates. While several machine learning models have been developed to analyze its causal factors, interpretations those remain opaque. In this paper, we propose HR-DSS approach, which stands for Human Resource (HR) Decision Support System, uses explainable AI employee problems. The system is designed assist HR departments in interpreting predictions provided by...
Abstract Answering factual questions from heterogenous sources, such as graphs and text, is a key capacity of intelligent systems. Current approaches either (i) perform question answering over text structured sources separate pipelines followed by merge step or (ii) provide an early integration, giving up the strengths particular information sources. To solve this problem, we present “HumanIQ”, method that teaches language models to dynamically combine retrieved imitating how humans use...
The way how research is communicated using text publications has not changed much over the past decades. We have vision that ultimately researchers will work on a common structured knowledge base comprising comprehensive semantic and machine-comprehensible descriptions of their research, thus making contributions more transparent comparable. present SemSur ontology for semantically capturing information commonly found in survey review articles. able to represent scientific results publish...
Knowledge graphs (KGs) are widely used for modeling scholarly communication, performing scientometric analyses, and supporting a variety of intelligent services to explore the literature predict research dynamics. However, they often suffer from incompleteness (e.g., missing affiliations, references, topics), leading reduced scope quality resulting analyses. This issue is usually tackled by computing knowledge graph embeddings (KGEs) applying link prediction techniques. only few KGE models...