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Data-centric intelligent information integration-from concepts to automation

机译:以数据为中心的智能信息集成-从概念到自动化

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Intelligent integration of information continues to challenge database research for over 35 years. While data integration processes of all kinds are now reasonably well understood and widely used in practice, the growth and heterogeneity of data requires much higher degrees of automation to limit the need for human specialist work. This requires deeper insights in data-centric approaches of Enterprise Information Integration which focus on the semantics of information integration. Recent formalizations and algorithms enable both significant improvement in schema integration, and in its automated transformation to efficient data-level integration, in a wide variety of architectural settings such as data warehouses or peer-to-peer databases. In addition to giving a short overview of developments in this field for the past 20 years, this paper focuses particularly on the challenges posed by heterogeneity in data models.
机译:超过35年以来,信息的智能集成一直在挑战数据库研究。尽管现在已经很好地理解了各种数据集成过程并在实践中广泛使用了这些数据,但是数据的增长和异构性要求更高的自动化程度,以限制对人类专家工作的需求。这就需要对以信息为中心的企业信息集成方法有更深入的了解,这些方法关注信息集成的语义。最近的形式化和算法可以在各种体系结构设置(例如数据仓库或对等数据库)中实现模式集成及其从自动转换为有效数据级别集成的显着改进。除了简要概述过去20年中该领域的发展外,本文还特别关注数据模型中异构性带来的挑战。

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