Remembering the Important Things: Semantic Importance in Stream Reasoning

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Reasoning and querying over data streams rely on the ability to deliver a sequence of stream snapshots to the processing algorithms.

These snapshots are typically provided using windows as views into streams and associated window management strategies.

In this work, we explore a general notion of \textit{semantic importance} that can be used for window management of RDF streaming data using semantically-aware processing algorithms.

Semantic importance exploits the information in RDF streams and surrounding ontologies for ranking window data in terms of its contribution to solution mappings.

We also consider how a stream window management strategy based on semantic importance could improve overall processing performance, especially as available window sizes decrease.


DateCreated ByLink
August 30, 2016
Rui YanDownload

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