Algorithmic Techniques for Processing Data Streams

Ikonomovska, Elena; Zelke, Mariano

doi:10.4230/DFU.Vol5.10452.237

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Algorithmic Techniques for Processing Data Streams

Authors Elena Ikonomovska, Mariano Zelke

Part of: Volume: Data Exchange, Integration, and Streams (DFU - Vol. 5)
Part of: Series: Dagstuhl Follow-Ups (DFU)
License: Creative Commons Attribution 3.0 Unported license
Publication Date: 2013-10-18

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DFU.Vol5.10452.237.pdf

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Document Identifiers

DOI: 10.4230/DFU.Vol5.10452.237
URN: urn:nbn:de:0030-drops-42968

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Keywords

streaming algorithm
sampling
sketching
group testing
histogram

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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) https://doi.org/10.4230/DFU.Vol5.10452.237

Author Details

Elena Ikonomovska

Mariano Zelke

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