数据集成的补并

Jens Bleiholder, Sascha Szott, Melanie Herschel, Felix Naumann
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引用次数: 9

摘要

数据集成过程包括将源数据映射为目标表示(模式映射[1]),识别同一真实世界对象的多个表示(重复检测[2]),最后将这些表示组合为单个一致的表示(数据融合[3])。显然,由于对象的多个表示通常不完全相等,因此在数据融合过程中,我们必须特别注意处理数据冲突。本文重点讨论了补并算子的定义和实现,它为数据融合定义了一种新的语义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complement union for data integration
A data integration process consists of mapping source data into a target representation (schema mapping [1]), identifying multiple representations of the same real-word object (duplicate detection [2]), and finally combining these representations into a single consistent representation (data fusion [3]). Clearly, as multiple representations of an object are generally not exactly equal, during data fusion, we have to take special care in handling data conflicts. This paper focuses on the definition and implementation of complement union, an operator that defines a new semantics for data fusion.
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