Sökning: "Computer Science with specialization in Database Technology"
Visar resultat 6 - 10 av 11 avhandlingar innehållade orden Computer Science with specialization in Database Technology.
6. Real-time data stream clustering over sliding windows
Sammanfattning : In many applications, e.g. urban traffic monitoring, stock trading, and industrial sensor data monitoring, clustering algorithms are applied on data streams in real-time to find current patterns. Here, sliding windows are commonly used as they capture concept drift. LÄS MER
7. Semantic Web Queries over Scientific Data
Sammanfattning : Semantic Web and Linked Open Data provide a potential platform for interoperability of scientific data, offering a flexible model for providing machine-readable and queryable metadata. However, RDF and SPARQL gained limited adoption within the scientific community, mainly due to the lack of support for managing massive numeric data, along with certain other important features – such as extensibility with user-defined functions, query modularity, and integration with existing environments and workflows. LÄS MER
8. Scalable Preservation, Reconstruction, and Querying of Databases in terms of Semantic Web Representations
Sammanfattning : This Thesis addresses how Semantic Web representations, in particular RDF, can enable flexible and scalable preservation, recreation, and querying of databases.An approach has been developed for selective scalable long-term archival of relational databases (RDBs) as RDF, implemented in the SAQ (Semantic Archive and Query) system. LÄS MER
9. Scalable Validation of Data Streams
Sammanfattning : In manufacturing industries, sensors are often installed on industrial equipment generating high volumes of data in real-time. For shortening the machine downtime and reducing maintenance costs, it is critical to analyze efficiently this kind of streams in order to detect abnormal behavior of equipment. LÄS MER
10. Scalable Parallelization of Expensive Continuous Queries over Massive Data Streams
Sammanfattning : Numerous applications in for example science, engineering, and financial analysis increasingly require online analysis over streaming data. These data streams are often of such a high rate that saving them to disk is not desirable or feasible. Therefore, search and analysis must be performed directly over the data in motion. LÄS MER