DFU.Vol5.10452.237.pdf
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Algorithmic Techniques for Processing Data Streams
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Volume:
Data Exchange, Integration, and Streams (DFU - Vol. 5)
Series: Dagstuhl Follow-Ups (DFU) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2013-10-18
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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
https://doi.org/10.4230/DFU.Vol5.10452.237
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.
Keywords
- streaming algorithm
- sampling
- sketching
- group testing
- histogram
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