Finding frequent items over sliding windows with constant update time

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23 Citations (Scopus)

Abstract

In this paper, we consider the problem of finding ε{lunate}-approximate frequent items over a sliding window of size N. A recent work by Lee and Ting (2006) [7] solves the problem by giving an algorithm that supports O (frac(1, ε{lunate})) query and update time, and uses O (frac(1, ε{lunate})) space. Their query time and memory usage are essentially optimal, but the update time is not. We give a new algorithm that supports O (1) update time with high probability while maintaining the query time and memory usage as O (frac(1, ε{lunate})).

Original languageEnglish
Pages (from-to)257-260
Number of pages4
JournalInformation Processing Letters
Volume110
Issue number7
DOIs
Publication statusPublished - 1 Mar 2010
Externally publishedYes

Keywords

  • Approximation algorithms
  • On-line algorithms

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