在基数和完整性约束下合成关联数据
Synthesizing Linked Data Under Cardinality and Integrity Constraints
摘要：
合成数据的生成在多个方面都很有用，从测试应用程序到基准测试再到隐私保护。在基数约束和完整性约束下生成关系之间的链接是这个问题的一个重要方面。给定两个关系的实例，其中一个关系具有对另一个关系的外键依赖性，并且缺少其外键（$FK$）值，以及两种类型的约束：（1）应用于联接视图的CC和（2）应用于缺少$FK$值的表的IC，我们的目标是估算缺少的$FK$值，使得满足约束。我们提供了一个新的框架的基础上声明CC和IC的问题。我们进一步表明，该问题是NP-难的，并提出了一种新的两阶段的解决方案，保证满意的IC。第一阶段产生了一个中间解决方案占CC单独，并依赖于一个混合的方法，基于CC类型。对于一种类型，问题被建模为一个线性规划。对于其他人，我们描述了一个有效和准确的解决方案。然后我们将两种解决方案结合起来。阶段II通过合并IC来增强该解决方案，并使用冲突超图的着色来推断$FK$列的值。我们广泛的实验研究表明，我们的解决方案的规模以及当数据和约束的数量增加。我们进一步表明，我们的解决方案保持低出错率的CC。
英文摘要：
The generation of synthetic data is useful in multiple aspects, from testing applications to benchmarking to privacy preservation. Generating the links between relations, subject to cardinality constraints (CCs) and integrity constraints (ICs) is an important aspect of this problem. Given instances of two relations, where one has a foreign key dependence on the other and is missing its foreign key ($FK$) values, and two types of constraints: (1) CCs that apply to the join view and (2) ICs that apply to the table with missing $FK$ values, our goal is to impute the missing $FK$ values such that the constraints are satisfied. We provide a novel framework for the problem based on declarative CCs and ICs. We further show that the problem is NP-hard and propose a novel two-phase solution that guarantees the satisfaction of the ICs. Phase I yields an intermediate solution accounting for the CCs alone, and relies on a hybrid approach based on CC types. For one type, the problem is modeled as an Integer Linear Program. For the others, we describe an efficient and accurate solution. We then combine the two solutions. Phase II augments this solution by incorporating the ICs and uses a coloring of the conflict hypergraph to infer the values of the $FK$ column. Our extensive experimental study shows that our solution scales well when the data and number of constraints increases. We further show that our solution maintains low error rates for the CCs.
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