映射和清理

Floris Geerts, G. Mecca, Paolo Papotti, Donatello Santoro
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引用次数: 50

摘要

我们解决了将数据集成和数据质量中的两个关键活动结合在一起的具有挑战性和开放性的问题,即使用模式映射转换数据,以及使用数据修复修复冲突和不一致。几个因素使这个问题变得复杂。首先,模式映射和数据修复传统上被认为是两个独立的活动,这两个领域的研究在很大程度上是独立的。其次,为这两个任务提出的优雅的形式化和算法在扩展到大型数据库时好坏参半。在本文中,我们介绍了映射和清理场景的一个非常一般的概念,它包含了各种各样的特征,例如,用户干预。我们为这些场景开发了一种新的语义,它代表了先前用于模式映射和数据修复的语义的保守扩展。在语义的基础上,引入了一种基于追逐的求解算法。适当的关注致力于开发可扩展的chase算法实现。据我们所知,这是第一个在这个方向上的通用和可扩展的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping and cleaning
We address the challenging and open problem of bringing together two crucial activities in data integration and data quality, i.e., transforming data using schema mappings, and fixing conflicts and inconsistencies using data repairing. This problem is made complex by several factors. First, schema mappings and data repairing have traditionally been considered as separate activities, and research has progressed in a largely independent way in the two fields. Second, the elegant formalizations and the algorithms that have been proposed for both tasks have had mixed fortune in scaling to large databases. In the paper, we introduce a very general notion of a mapping and cleaning scenario that incorporates a wide variety of features, like, for example, user interventions. We develop a new semantics for these scenarios that represents a conservative extension of previous semantics for schema mappings and data repairing. Based on the semantics, we introduce a chase-based algorithm to compute solutions. Appropriate care is devoted to developing a scalable implementation of the chase algorithm. To the best of our knowledge, this is the first general and scalable proposal in this direction.
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