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Issue No. 01 - January/February (2012 vol. 29)
ISSN: 0740-7459
pp: 64-69
Muthu Muthukrishnan , Rutgers University
Graham Cormode , AT&T Labs-Research
ABSTRACT
Faced with handling multiple large data sets in modern data-processing settings, researchers have proposed sketch data structures that capture salient properties while occupying little memory and that update or probe quickly. In particular, the Count-Min sketch has proven effective for a variety of applications. It concurrently tracks many item counts with surprisingly strong accuracy.
INDEX TERMS
Count-Min sketch, massive data, streaming algorithms, software engineering
CITATION
Muthu Muthukrishnan, Graham Cormode, "Approximating Data with the Count-Min Sketch", IEEE Software, vol. 29, no. , pp. 64-69, January/February 2012, doi:10.1109/MS.2011.127
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