Holistic Statistical Open Data integration based on integer linear programming

2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS) Pub Date : 2015-05-13 DOI:10.1109/RCIS.2015.7128908

A. Berro, I. Megdiche, O. Teste

{"title":"Holistic Statistical Open Data integration based on integer linear programming","authors":"A. Berro, I. Megdiche, O. Teste","doi":"10.1109/RCIS.2015.7128908","DOIUrl":null,"url":null,"abstract":"Integrating several Statistical Open Data (SOD) tables is a very promising issue. Various analysis scenarios are hidden behind these statistical data, which makes it important to have a holistic view of them. However, as these data are scattered in several tables, it is a slow and costly process to use existing pairwise schema matching approaches to integrate several schemas of the tables. Hence, we need automatic tools that rapidly converge to a holistic integrated view of data and give a good matching quality. In order to accomplish this objective, we propose a new 0-1 linear program, which automatically resolves the problem of holistic OD integration. It performs global optimal solutions maximizing the profit of similarities between OD graphs. The program encompasses different constraints related to graph structures and matching setup, in particular 1:1 matching. It is solved using a standard solver (CPLEX) and experiments show that it can handle several input graphs and good matching quality compared to existing tools.","PeriodicalId":244105,"journal":{"name":"2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCIS.2015.7128908","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

Abstract

Integrating several Statistical Open Data (SOD) tables is a very promising issue. Various analysis scenarios are hidden behind these statistical data, which makes it important to have a holistic view of them. However, as these data are scattered in several tables, it is a slow and costly process to use existing pairwise schema matching approaches to integrate several schemas of the tables. Hence, we need automatic tools that rapidly converge to a holistic integrated view of data and give a good matching quality. In order to accomplish this objective, we propose a new 0-1 linear program, which automatically resolves the problem of holistic OD integration. It performs global optimal solutions maximizing the profit of similarities between OD graphs. The program encompasses different constraints related to graph structures and matching setup, in particular 1:1 matching. It is solved using a standard solver (CPLEX) and experiments show that it can handle several input graphs and good matching quality compared to existing tools.

查看原文本刊更多论文

基于整数线性规划的整体统计开放数据集成

集成多个统计开放数据(SOD)表是一个非常有前途的问题。这些统计数据背后隐藏着各种各样的分析场景，这使得对它们有一个整体的看法变得很重要。但是，由于这些数据分散在几个表中，因此使用现有的成对模式匹配方法来集成表的多个模式是一个缓慢而昂贵的过程。因此，我们需要能够快速收敛到数据的整体集成视图并提供良好匹配质量的自动工具。为了实现这一目标，我们提出了一种新的0-1线性规划，该规划能够自动解决整体OD集成问题。它执行全局最优解，使OD图之间的相似度利润最大化。该程序包含与图结构和匹配设置相关的不同约束，特别是1:1匹配。使用标准求解器(CPLEX)对其进行求解，实验表明，与现有工具相比，它可以处理多个输入图，并且具有良好的匹配质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2015 IEEE 9th International Conference on Research Challenges in Information Science (RCIS)

自引率

0.00%

发文量