Frames : Data-driven Windows

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GROSSNIKLAUS, Michael, David MAIER, James MILLER, Sharmadha MOORTHY, Kristin TUFTE, 2016. Frames : Data-driven Windows. 10th ACM International Conference on Distributed and Event-Based Systems. Irvine, CA, USA, Jun 20, 2016 - Jun 24, 2016. In: Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS). New York, NY:ACM, pp. 13-24. ISBN 978-1-4503-4021-2. Available under: doi: 10.1145/2933267.2933304

@inproceedings{Grossniklaus2016Frame-33848, title={Frames : Data-driven Windows}, year={2016}, doi={10.1145/2933267.2933304}, isbn={978-1-4503-4021-2}, address={New York, NY}, publisher={ACM}, booktitle={Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS)}, pages={13--24}, author={Grossniklaus, Michael and Maier, David and Miller, James and Moorthy, Sharmadha and Tufte, Kristin} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <bibo:uri rdf:resource=""/> <dc:contributor>Tufte, Kristin</dc:contributor> <dc:rights>terms-of-use</dc:rights> <dc:creator>Grossniklaus, Michael</dc:creator> <dcterms:available rdf:datatype="">2016-05-09T15:47:36Z</dcterms:available> <dcterms:hasPart rdf:resource=""/> <dc:creator>Miller, James</dc:creator> <dc:creator>Moorthy, Sharmadha</dc:creator> <dc:contributor>Grossniklaus, Michael</dc:contributor> <dcterms:abstract xml:lang="eng">Traditional Data Stream Management Systems (DSMS) segment data streams using windows that are defined either by a time interval or a number of tuples. Such windows are fixed—the definition unvarying over the course of a stream—and are defined based on external properties unrelated to the data content of the stream. However, streams and their con- tent do vary over time—the rate of a data stream may vary or the data distribution of the content may vary. The mismatch between a fixed stream segmentation and a variable stream motivates the need for a more flexible, expressive and physically independent stream segmentation. We introduce a new stream segmentation technique, called frames. Frames segment streams based on data content. We present a theory and implementation of frames and show the utility of frames for a variety of applications.</dcterms:abstract> <dcterms:title>Frames : Data-driven Windows</dcterms:title> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:language>eng</dc:language> <dspace:hasBitstream rdf:resource=""/> <dc:creator>Tufte, Kristin</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:rights rdf:resource=""/> <dcterms:issued>2016</dcterms:issued> <dc:creator>Maier, David</dc:creator> <dcterms:isPartOf rdf:resource=""/> <dc:contributor>Maier, David</dc:contributor> <dc:date rdf:datatype="">2016-05-09T15:47:36Z</dc:date> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Miller, James</dc:contributor> <dc:contributor>Moorthy, Sharmadha</dc:contributor> </rdf:Description> </rdf:RDF>

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