ROCK Algorithm Parallelization with TOREADOR Primitives

B. D. Martino, Salvatore D'Angelo, A. Esposito, Riccardo Cappuzzo, Anderson Santana de Oliveira
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引用次数: 1

Abstract

We present the benefits of applying the code once deploy everywhere approach to clustering of categorical data over large datasets. The paper brings two main contributions: an step-by step application of the code based approach and an enhancement for the ROCK algorithm for clustering categorical data.
TOREADOR基元的ROCK算法并行化
我们介绍了应用代码一次部署无处不在的方法对大型数据集上的分类数据进行聚类的好处。本文带来了两个主要贡献:基于代码的逐步应用方法和对ROCK算法的改进,用于分类数据的聚类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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