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We propose an intelligent and an efficient query processing approach for semantic mediation of information systems.
We discuss how scqd metadata can be organized in partially ordered sets to support efficient query processing.
Our distributed PDCR tree data structure supports multiple dimension hierarchies and efficient query processing on the elaborate dimension hierarchies which are so central to OLAP systems.
Second, a new indexing structure, which is designed to support the inverted-space storage organization, enables efficient query processing in projected spaces with moderate dimensionality.
In particular, designing an efficient query processing scheme is admittedly challenging in mobile ad hoc networks (MANETs) because of the lack of centralized coordination, limited computing and communication capabilities, and time-varying network topologies.
A spatial indexing structure is built to provide fast data access and in turn, efficient query processing.
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In this study, we report our recent efforts on this issue, with a focus on energy-aware query optimization and energy-efficient query processing.
Replicating data fragments from different sources enables data re-organization and provides the basis for more effective and efficient federated query processing.
Performance is evaluated by experimental methods and two case studies serve to show how to develop efficient parallel query processing algorithms for large-scale search engines based on the proposed paradigm.
At first, these methods were tailored to provide efficient similarity queries processing.
Context broker query processing.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com