Extracting correlated parameters on multicore architectures

Abstract : In this paper, we present a new approach relevant to the discovery of correlated patterns, based on the use of multicore architectures. Our work rests on a full KDD system and allows one to extract Decision Correlation Rules based on the Chi-squared criterion that include a target column from any database. To achieve this objective, we use a levelwise algorithm as well as contingency vectors, an alternate and more powerful representation of contingency tables, in order to prune the search space. The goal is to parallelize the processing associated with the extraction of relevant rules. The parallelization invokes the PPL (Parallel Patterns Library), which allows a simultaneous access to the whole available cores / processors on modern computers. We nally present rst results on the reached performance gains.
Type de document :
Communication dans un congrès
CD-ARES 2013, Sep 2013, Regensburg, Italy. Springer, pp 118-133, 2013, LNCS
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Contributeur : Christian Ernst <>
Soumis le : vendredi 20 décembre 2013 - 17:14:49
Dernière modification le : mercredi 19 décembre 2018 - 13:08:13
Document(s) archivé(s) le : vendredi 21 mars 2014 - 09:19:33


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  • HAL Id : emse-00921635, version 1


Christian Ernst, Alain Casali. Extracting correlated parameters on multicore architectures. CD-ARES 2013, Sep 2013, Regensburg, Italy. Springer, pp 118-133, 2013, LNCS. 〈emse-00921635〉



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