Real-Time Entity Resolution by Forest-Based Indexing in Database Systems with Vertical Fragmentations

Liang Zhu, Jiapeng Yang, Xin Song, Yu Wang, Yonggang Wei
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Abstract

Entity resolution (ER) is the process of identifying and matching which tuples/records in a dataset/relation refer to the same real-world entity. Real-time ER is a challenge for large datasets. Schema decomposition is of importance in (distributed) database systems, which partitions a relation/table into a set of vertical fragmentations. For this scenario, we study real-time ER in this paper. By creating forest-based indexing and defining ranking functions and corresponding algorithms, we propose an approach to resolve query tuples over dirty relations of a set of vertical fragmentations with duplicates, misspellings, or NULL values of text attributes. Extensive experiments are conducted to demonstrate the performances of our proposed approach.
垂直碎片数据库系统中基于森林索引的实时实体解析
实体解析(ER)是识别和匹配数据集/关系中哪些元组/记录引用相同的现实世界实体的过程。实时ER对大型数据集来说是一个挑战。模式分解在(分布式)数据库系统中非常重要,它将关系/表划分为一组垂直片段。针对这一场景,本文研究了实时ER。通过创建基于森林的索引并定义排序函数和相应的算法,我们提出了一种方法来解决一组具有文本属性的重复、拼写错误或NULL值的垂直碎片的脏关系上的查询元组。大量的实验证明了我们提出的方法的性能。
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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