PGP-mc: Towards a Multicore Parallel Approach for Mining Gradual Patterns

被引：0

作者：

Laurent, Anne ^{[1
]}

Negrevergne, Benjamin ^{[2
]}

Sicard, Nicolas ^{[3
]}

Termier, Alexandre ^{[2
]}

机构：

[1] UM2, LIRMM, CNRS, UMR 5506, 161 Rue Ada, F-34392 Montpellier 5, France

[2] UJF, LIG, CNRS, UMR 5217, F-38402 St Martin Dheres, France

[3] LRIE, EFREI, F-94800 Villejuif, France

来源：

DATABASE SYSTEMS FOR ADVANCED APPLICATIONS, PT I, PROCEEDINGS | 2010年 / 5981卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Gradual patterns highlight complex order correlations of the form "The more/less X. the more/less Y". Only recently algorithms have appeared to mine efficiently gradual rules. However, due to the complexity of milling gradual rules, these algorithms cannot yet scale on huge real world datasets. hi this paper, we propose to exploit parallelism in order to enhance the performances of the fastest existing one (GRITE). Through a detailed experimental study, we show that our parallel algorithm scales very well with the number of cores available.

引用

页码：78 / +

页数：2

共 9 条

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