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.

Autore Pugliese

• Cafaro Massimo , Epicoco Italo

Tutti gli autori

• Epicoco I. , Cafaro M. , Pulimeno M.

Titolo volume/Rivista

DATA MINING AND KNOWLEDGE DISCOVERY

Anno di pubblicazione

2018

ISSN

1384-5810

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

0

Ultimo Aggiornamento Citazioni

28/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile