一种基于欧洲地理网格的四叉树方法:协调数据隐私和准确性

IF 0.7 4区数学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Sort-Statistics and Operations Research Transactions Pub Date : 2017-06-21 DOI:10.2436/20.8080.02.55

R. Lagonigro, Ramon Oller, J. Martori

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引用次数: 7

摘要

在发布地理信息时，保护机密性的方法与发布准确数据的需要相冲突。本文的目标是创建一个欧洲地理网格框架——通过地图传播统计数据。我们提出了一种基于四叉树分层地理数据结构的方法。我们创建了一个适应局部区域密度的不同大小的网格。人口稠密的地区被划分成小方块，以便传播准确的数据。另外，人口稀少地区的信息以大方格发布，以避免识别单个数据。该方法已应用于2014年加泰罗尼亚人口登记数据

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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A quadtree approach based on European geographic grids: reconciling data privacy and accuracy

Methods to preserve confidentiality when publishing geographic information conflict with the need to publish accurate data. The goal of this paper is to create a European geographic grid frame- work to disseminate statistical data over maps. We propose a methodology based on quadtree hierarchical geographic data structures. We create a varying size grid adapted to local area densities. High populated zones are disaggregated in small squares to allow dissemination of accurate data. Alternatively, information on low populated zones is published in big squares to avoid identification of individual data. The methodology has been applied to the 2014 population register data in Catalonia

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来源期刊

Sort-Statistics and Operations Research Transactions 管理科学-统计学与概率论

CiteScore

3.10

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： SORT (Statistics and Operations Research Transactions) —formerly Qüestiió— is an international journal launched in 2003. It is published twice-yearly, in English, by the Statistical Institute of Catalonia (Idescat). The journal is co-edited by the Universitat Politècnica de Catalunya, Universitat de Barcelona, Universitat Autonòma de Barcelona, Universitat de Girona, Universitat Pompeu Fabra i Universitat de Lleida, with the co-operation of the Spanish Section of the International Biometric Society and the Catalan Statistical Society. SORT promotes the publication of original articles of a methodological or applied nature or motivated by an applied problem in statistics, operations research, official statistics or biometrics as well as book reviews. We encourage authors to include an example of a real data set in their manuscripts.