License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
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DOI: 10.4230/DFU.Vol5.10452.237
URN: urn:nbn:de:0030-drops-42968
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Ikonomovska, Elena ; Zelke, Mariano

Algorithmic Techniques for Processing Data Streams

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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.

BibTeX - Entry

  author =	{Elena Ikonomovska and Mariano Zelke},
  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 =	{Phokion G. Kolaitis and Maurizio Lenzerini and Nicole Schweikardt},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-42968},
  doi =		{10.4230/DFU.Vol5.10452.237},
  annote =	{Keywords: streaming algorithm, sampling, sketching, group testing, histogram}

Keywords: streaming algorithm, sampling, sketching, group testing, histogram
Collection: Data Exchange, Integration, and Streams
Issue Date: 2013
Date of publication: 18.10.2013

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