On the complexity of finding set repairs for data-graphs
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 52 references that are in the map. First posted on arXiv 15 Jun 2022.
Builds on
5 of 52 references.
References · 5
- 2020Knowledge Graphscited by 619
- 2016Foundations of Modern Query Languages for Graph Databasescited by 22
- 2017G-CORE: A Core for Future Graph Query Languagescited by 13
- 2016Complexity of Consistent Query Answering in Databases under Cardinality-Based and Incremental Repair Semantics (extended version)cited by 12
- 2018Finite Query Answering in Expressive Description Logics with Transitive Rolescited by 4
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