关于寻找数据图集合修复的复杂度
On the complexity of finding set repairs for data-graphs
AI总结：
本文研究了在基于 Reg-GXPath 表达式作为完整性约束的条件下，为带有数据值的图数据库计算子集和超集修复的复杂度，证明了正片段存在多项式时间算法，而全语言表达能力则使问题难以处理。
摘要：
在我们身处的深度互联世界中，信息片段将我们周围的各个领域链接起来。由于图数据库能够有效处理数据间的关系，并允许高效地处理和查询这些连接，它们正迅速成为支持广泛领域和应用的流行存储平台。与关系型数据库的情况一样，我们期望数据能够保留一组完整性约束，这些约束定义了其所表示的世界的语义结构。当数据库不满足其完整性约束时，一种可能的方法是寻找一个满足约束的“相似”数据库，这也被称为修复。在本研究中，我们研究了使用基于一组 Reg-GXPath 表达式作为完整性约束的一致性概念，为带有数据值的图数据库计算子集和超集修复的问题。我们证明，对于 Reg-GXPath 的正片段，这些问题存在多项式时间算法，而该语言的全部表达能力则使它们变得难以处理。
英文摘要：
In the deeply interconnected world we live in, pieces of information link domains all around us. As graph databases embrace effectively relationships among data and allow processing and querying these connections efficiently, they are rapidly becoming a popular platform for storage that supports a wide range of domains and applications. As in the relational case, it is expected that data preserves a set of integrity constraints that define the semantic structure of the world it represents. When a database does not satisfy its integrity constraints, a possible approach is to search for a 'similar' database that does satisfy the constraints, also known as a repair. In this work, we study the problem of computing subset and superset repairs for graph databases with data values using a notion of consistency based on a set of Reg-GXPath expressions as integrity constraints. We show that for positive fragments of Reg-GXPath these problems admit a polynomial-time algorithm, while the full expressive power of the language renders them intractable.
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