Joint Entity Resolution

Steven Euijong Whang, H. Garcia-Molina
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引用次数: 44

Abstract

Entity resolution (ER) is the problem of identifying which records in a database represent the same entity. Often, records of different types are involved (e.g., authors, publications, institutions, venues), and resolving records of one type can impact the resolution of other types of records. In this paper we propose a flexible, modular resolution framework where existing ER algorithms developed for a given record type can be plugged in and used in concert with other ER algorithms. Our approach also makes it possible to run ER on subsets of similar records at a time, important when the full data is too large to resolve together. We study the scheduling and coordination of the individual ER algorithms in order to resolve the full data set. We then evaluate our joint ER techniques on synthetic and real data and show the scalability of our approach.
联合实体决议
实体解析(ER)是识别数据库中哪些记录代表同一实体的问题。通常,涉及不同类型的记录(例如,作者、出版物、机构、场所),解决一种类型的记录可能会影响其他类型记录的解决。在本文中,我们提出了一个灵活的模块化解决框架,其中为给定记录类型开发的现有ER算法可以插入并与其他ER算法一起使用。我们的方法还可以一次在类似记录的子集上运行ER,这在完整数据太大而无法一起解析时非常重要。为了解决完整的数据集,我们研究了各个ER算法的调度和协调。然后,我们在合成数据和真实数据上评估了我们的联合ER技术,并展示了我们方法的可扩展性。
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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