A 2/sup d/-tree-based blocking method for microaggregating very large data sets

A. Solanas, A. Martmez-Balleste, J. Domingo-Ferrer, J. M. Mateo-Sanz
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引用次数: 15

Abstract

Blocking is a well-known technique used to partition a set of records into several subsets of manageable size. The standard approach to blocking is to split the records according to the values of one or several attributes (called blocking attributes). This paper presents a new blocking method based on 2/sup d/-trees for intelligently partitioning very large data sets for micro aggregation. A number of experiments has been carried out in order to compare our method with the most typical univariate one.
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一种基于2/sup /-tree的阻塞方法,用于微聚合非常大的数据集
阻塞是一种众所周知的技术,用于将一组记录划分为几个可管理大小的子集。阻塞的标准方法是根据一个或多个属性(称为阻塞属性)的值拆分记录。本文提出了一种基于2/sup /-树的块化方法,用于对超大数据集进行微聚合智能分区。为了将我们的方法与最典型的单变量方法进行比较,进行了许多实验。
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