Order dependencies (ODs) capture relationships between ordered domains of attributes. Approximate ODs (AODs) capture such relationships even when there exist exceptions in the data. During automated discovery of ODs, validation is the process of verifying whether an OD holds. We present an algorithm for validating approximate ODs with significantly improved runtime performance over existing methods for AODs, and prove that it is correct and has optimal runtime. By replacing the validation step in a leading algorithm for approximate OD discovery with ours, we achieve orders-of-magnitude improvements in performance.

中文翻译：

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高效发现近似订单依存关系

顺序依赖关系（OD）捕获属性的有序域之间的关系。即使数据中存在异常，近似OD（AOD）也会捕获此类关系。在自动发现OD的过程中，验证是验证OD是否成立的过程。我们提出了一种用于验证近似OD的算法，该算法比现有的AOD方法具有显着提高的运行时性能，并证明它是正确的并且具有最佳的运行时。通过用我们的算法替换领先的近似OD发现算法中的验证步骤，我们实现了性能的数量级改进。