Issue No. 01 - January/February (2012 vol. 29)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MS.2011.127
Graham Cormode , AT&T Labs-Research
Muthu Muthukrishnan , Rutgers University
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.
Count-Min sketch, massive data, streaming algorithms, software engineering
Graham Cormode, Muthu Muthukrishnan, "Approximating Data with the Count-Min Sketch", IEEE Software, vol. 29, no. , pp. 64-69, January/February 2012, doi:10.1109/MS.2011.127