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A Survey of Cognitive Theories to Support Data Integration

机译:支持数据集成的认知理论研究

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Business intelligence applications are being increasingly used to facilitate managerial insight and maintain competitiveness. These applications rely on the availability of integrated data from multiple data sources, making database integration an increasingly important task. A central step in the process of data integration is schema matching, the identification of similar elements in the two databases. While a number of approaches have been proposed, the majority of schema matching techniques are based on ad-hoc heuristics, instead of an established theoretical foundation. The absence of a theoretical foundation makes it difficult to explain and improve schema matching process. This research surveys current cognitive theories of similarity and demonstrates their application to the problem of schema matching. Better integration techniques will benefit business intelligence applications and can thereby contribute to business value.
机译:商业智能应用程序越来越多地用于促进管理洞察力和保持竞争力。这些应用程序依赖于来自多个数据源的集成数据的可用性,从而使数据库集成变得越来越重要。数据集成过程中的中心步骤是模式匹配,即在两个数据库中识别相似的元素。虽然已经提出了许多方法,但是大多数模式匹配技术都是基于即席启发式方法,而不是已建立的理论基础。由于缺乏理论基础,因此难以解释和改进模式匹配过程。这项研究调查了当前的相似性认知理论,并论证了它们在图式匹配问题中的应用。更好的集成技术将使商业智能应用程序受益,从而可以为商业价值做出贡献。

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