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Tutorial: Uncertain Entity Resolution: Re-evaluating Entity Resolution in the Big Data Era

机译:教程:不确定的实体分辨率:在大数据时代重新评估实体的分辨率

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Entity resolution is a fundamental problem in data integration dealing with the combination of data from different sources to a unified view of the data. Entity resolution is inherently an uncertain process because the decision to map a set of records to the same entity cannot be made with certainty unless these are identical in all of their attributes or have a common key. In the light of recent advancement in data accumulation, management, and analytics landscape (known as big data) the tutorial re-evaluates the entity resolution process and in particular looks at best ways to handle data veracity. The tutorial ties entity resolution with recent advances in probabilistic database research, focusing on sources of uncertainty in the entity resolution process.
机译:实体解析是数据集成中的一个基本问题,处理来自不同来源的数据组合到数据的统一视图。实体解析从本质上来说是一个不确定的过程,因为除非将记录的所有属性都相同或具有共同的密钥,否则无法确定将记录集映射到同一实体的决定。鉴于数据累积,管理和分析领域(称为大数据)的最新发展,本教程重新评估了实体解析过程,并特别探讨了处理数据准确性的最佳方法。本教程将实体解析与概率数据库研究的最新进展联系在一起,重点关注实体解析过程中的不确定性来源。

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