A5056874914- Semantic Web and Ontologies
- Advanced Database Systems and Queries
- Data Quality and Management
- Advanced Graph Neural Networks
- Library Science and Information Systems
- Data Management and Algorithms
- Biomedical Text Mining and Ontologies
- Natural Language Processing Techniques
- Graph Theory and Algorithms
- Data Mining Algorithms and Applications
- Service-Oriented Architecture and Web Services
- Cognitive Computing and Networks
- Advanced Control Systems Optimization
- Land Use and Ecosystem Services
- Network Security and Intrusion Detection
- Urban Transport and Accessibility
- Image Processing and 3D Reconstruction
- Logic, Reasoning, and Knowledge
- Web Data Mining and Analysis
- Rough Sets and Fuzzy Logic
- Process Optimization and Integration
- Distributed systems and fault tolerance
- Urban Green Space and Health
- Advanced Multi-Objective Optimization Algorithms
Karlsruhe Institute of Technology
2017-2022
Robert Bosch (Germany)
2022
Kentucky imaging Technologies (United States)
2021
Institute of Soil Science
2016
Linked Data Fragments (LDFs) are Web interfaces that enable querying knowledge graphs on the Web. These interfaces, such as SPARQL endpoints or Triple Pattern Fragment servers, differ in expressions they can evaluate and metadata provide. So far, federated query processing has focused federations with a single type of LDF interface, typically endpoints. In this work, we address challenges over heterogeneous interfaces. To end, propose an interface-aware framework illustrate its applicability...
Scalarization functions represent preferences in multi-objective optimization by mapping the vector of objectives to a single real value. Optimization techniques using scalarized mainly focus on obtaining only global preference optimum. Instead, we propose considering all local and scalarization optima Pareto front. These points best choice their immediate neighborhood. Additionally, they are usually sufficiently far apart objective space present themselves as true alternatives if function...
Linked Data Fragments (LDFs) refer to interfaces that allow for publishing and querying Knowledge Graphs on the Web. These primarily differ in their expressivity exploring different trade-offs when balancing workload between clients servers decentralized SPARQL query processing. To devise efficient plans, typically rely heuristics leverage metadata provided by LDF interface, since obtaining fine-grained statistics from remote sources is a challenging task. However, these are prone potential...
Research on environmental justice comprises health and well-being aspects, as well topics related to general social participation. In this research field, among others, there is a need for an integrated use of science survey data spatial data, e.g. combining demographic information from with pollution data. However, researchers it challenging link both sources, because (1) the interdisciplinary nature sources different, (2) underlie different legal restrictions, in particular regarding...
RDF dataset profiling is the task of extracting a formal representation dataset’s features. Such features may cover various aspects ranging from information on licensing and provenance to statistical descriptors data distribution its semantics. In this work, we focus characteristics sets profile that capture both structural semantic an dataset, making them valuable resource for different downstream applications. While previous research demonstrated benefits characteristic in centralized...
Linked Data Fragments (LDFs) refer to Web interfaces that allow for accessing and querying Knowledge Graphs on the Web. These interfaces, such as SPARQL endpoints or Triple Pattern Fragment servers, differ in expressions they can evaluate metadata provide. Client-side query processing approaches have been proposed are tailored queries over individual interfaces. Moreover, federated has focused federations with a single type of LDF interface, typically endpoints. In this work, we address...
SPARQL endpoints are web services that allow for querying RDF knowledge graphs online using the query language. In 1.1, federation extension allows explicitly evaluating expressions of a at certain SERVICE keyword. However, current foundations federated processing rely on two central assumptions: (i) members assumed to be equal in terms quality, and (ii) strict definition answer completeness, where expression is evaluated over all relevant endpoints. These assumptions hinder scalability...