Projects per year
Abstract
The Semantic Web provides the simple but powful machnisms to describe information in a machine-understandable way and to enable automatic inference of new knowledge. These Semantic Web techniques are being widely applied in complex real-world applications, and more and more data, including data streams, are described using the Semantic Web technology. Streaming query engines evaluate queries on streams of data, and can discard irrelevant input earilier, build indices only on the data needed for the evaluation of the query, and determine partial results of a query as soon as they are available, in order to save processing costs and space costs, and to enable more efficient processing of queries. As well as querying the given data, querying Semantic Web data streams is involved with inferable data, which are not contained in the data streams. While the optimization techniques for querying data streams has been well studied, the optimization techniques for querying Semantic Web data streams is still an open research topic. We will address its challenges and future trends in this contribution.
Original language | English |
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Title of host publication | Data Mining and Management |
Number of pages | 15 |
Publisher | Nova Science Publishers, Inc. |
Publication date | 01.12.2010 |
Pages | 225-239 |
ISBN (Print) | 9781607412892 |
Publication status | Published - 01.12.2010 |
Research Areas and Centers
- Research Area: Intelligent Systems
- Centers: Center for Artificial Intelligence Luebeck (ZKIL)
DFG Research Classification Scheme
- 4.43-03 Security and Dependability, Operating, Communication and Distributed Systems
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Dive into the research topics of 'Challenges and future trends in querying semantic web data streams'. Together they form a unique fingerprint.Projects
- 1 Finished
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Logically and physically optimized Semantic Web database engine
Groppe, S. & Linnemann, V.
01.01.07 → 31.12.11
Project: DFG Projects › DFG Individual Projects