The problem of mining Correlated Heavy Hitters (CHH) from a two- dimensional data stream has been introduced recently, and a deterministic algo- rithm based on the use of the Misra–Gries algorithm has been proposed by Lahiri et al. to solve it. In this paper we present a new counter-based algorithm for tracking CHHs, formally prove its error bounds and correctness and show, through exten- sive experimental results, that our algorithm outperforms the Misra–Gries based algorithm with regard to accuracy and speed whilst requiring asymptotically much less space.

Fast and Accurate Mining of Correlated Heavy Hitters

EPICOCO, Italo
Methodology
;
CAFARO, Massimo
Methodology
;
PULIMENO, MARCO
Methodology
2018

Abstract

The problem of mining Correlated Heavy Hitters (CHH) from a two- dimensional data stream has been introduced recently, and a deterministic algo- rithm based on the use of the Misra–Gries algorithm has been proposed by Lahiri et al. to solve it. In this paper we present a new counter-based algorithm for tracking CHHs, formally prove its error bounds and correctness and show, through exten- sive experimental results, that our algorithm outperforms the Misra–Gries based algorithm with regard to accuracy and speed whilst requiring asymptotically much less space.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11587/413212
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