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Algorithmic Techniques for Processing Data Streams

Authors: Elena Ikonomovska and Mariano Zelke

Published in: Dagstuhl Follow-Ups, Volume 5, Data Exchange, Integration, and Streams (2013)

Abstract

We give a survey at some algorithmic techniques for processing data streams. After covering the basic methods of sampling and sketching, we present more evolved procedures that resort on those basic ones. In particular, we examine algorithmic schemes for similarity mining, the concept of group testing, and techniques for clustering and summarizing data streams.

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Elena Ikonomovska and Mariano Zelke. Algorithmic Techniques for Processing Data Streams. In Data Exchange, Integration, and Streams. Dagstuhl Follow-Ups, Volume 5, pp. 237-274, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InCollection{ikonomovska_et_al:DFU.Vol5.10452.237,
  author =	{Ikonomovska, Elena and Zelke, Mariano},
  title =	{{Algorithmic Techniques for Processing Data Streams}},
  booktitle =	{Data Exchange, Integration, and Streams},
  pages =	{237--274},
  series =	{Dagstuhl Follow-Ups},
  ISBN =	{978-3-939897-61-3},
  ISSN =	{1868-8977},
  year =	{2013},
  volume =	{5},
  editor =	{Kolaitis, Phokion G. and Lenzerini, Maurizio and Schweikardt, Nicole},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DFU.Vol5.10452.237},
  URN =		{urn:nbn:de:0030-drops-42968},
  doi =		{10.4230/DFU.Vol5.10452.237},
  annote =	{Keywords: streaming algorithm, sampling, sketching, group testing, histogram}
}

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Documents authored by Ikonomovska, Elena

Algorithmic Techniques for Processing Data Streams

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