On the Complexity of Finding Set Repairs for Data-Graphs (Abstract Reprint)
On the Complexity of Finding Set Repairs for Data-Graphs (Abstract Reprint)
Sergio Abriola, Maria Vanina Martinez, Nina Pardal, Santiago Cifuentes, Edwin Pin Baque
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
Journal Track. Pages 8472-8472.
https://doi.org/10.24963/ijcai.2024/944
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 having a set of Reg-GXPath expressions as integrity constraints.
We show that for positive fragments of Reg-GXPath these problems admit a polynomialtime algorithm, while the full expressive power of the language renders them intractable.
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Journal Track: Journal Track