• 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