数据清理和XML: DBLP体验

Wai Lup Low, W. Tok, M. Lee, T. Ling
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引用次数: 9

摘要

随着以数据为中心的XML的日益流行,正在为迅速发展的XML数据存储库开发数据仓库和挖掘应用程序。毫无疑问,数据质量将是此类应用程序成功的关键因素。数据清洗是指用于提高数据质量的过程,在传统数据库中已经得到了很好的研究。在早期的工作中,我们为数据清理关系数据库开发了一个基于知识的框架。在这项工作中,我们提出了一种将该框架应用于XML数据库的新颖尝试。我们的实验数据集是DBLP数据库,这是许多研究人员使用的一个流行的在线XML书目数据库。
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Data cleaning and XML: the DBLP experience
With the increasing popularity of data-centric XML, data warehousing and mining applications are being developed for rapidly burgeoning XML data repositories. Data quality will no doubt be a critical factor for the success of such applications. Data cleaning, which refers to the processes used to improve data quality, has been well researched in the context of traditional databases. In earlier work we developed a knowledge-based framework for data cleaning relational databases. In this work, we present a novel attempt to apply this framework to XML databases. Our experimental dataset is the DBLP database, a popular online XML bibliography database used by many researchers.
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