DocumentCode
1348252
Title
Approximating Data with the Count-Min Sketch
Author
Cormode, Graham ; Muthukrishnan, S.
Volume
29
Issue
1
fYear
2012
Firstpage
64
Lastpage
69
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.
Keywords
data handling; Count-Min sketch; data approximation; data set handling; data-processing setting; Data processing; Data structures; Large-scale systems; Software algorithms; Count-Min sketch; massive data; software engineering; streaming algorithms;
fLanguage
English
Journal_Title
Software, IEEE
Publisher
ieee
ISSN
0740-7459
Type
jour
DOI
10.1109/MS.2011.127
Filename
6042851
Link To Document