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On the data complexity of consistent query answering over graph databases

机译:关于逐渐查询回答的数据复杂性 - 通过图形数据库回答

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摘要

Areas in which graph databases are applied - such as the semantic web, social networks and scientific databases - are prone to inconsistency, mainly due to interoperability issues. This raises the need for understanding query answering over inconsistent graph databases in a framework that is simple yet general enough to accommodate many of its applications. We follow the well-known approach of consistent query answering (CQA), and study the data complexity of CQA over graph databases for regular path queries (RPQs) and regular path constraints (RPCs), which are frequently used. We concentrate on subset, superset and symmetric difference repairs. Without further restrictions, CQA is undecidable for the semantics based on superset and symmetric difference repairs, and Pi_2^P-complete for subset repairs. However, we provide several tractable restrictions on both RPCs and the structure of graph databases that lead to decidability, and even tractability of CQA. We also compare our results with those obtained for CQA in the context of relational databases.
机译:主要由于互操作性问题,应用了图数据库的区域(例如语义网,社交网络和科学数据库)容易出现不一致的情况。这就需要在一个简单而通用的框架中理解不一致图形数据库上的查询回答,从而足以容纳其许多应用程序。我们遵循一致查询回答(CQA)的众所周知的方法,并针对经常使用的常规路径查询(RPQ)和常规路径约束(RPC)研究图形数据库上CQA的数据复杂性。我们专注于子集,超集和对称差异修复。没有进一步的限制,对于基于超集和对称差异修复的语义,CQA是不确定的,对于子集修复,Pi_2 ^ P-complete是不确定的。但是,我们对RPC和图形数据库的结构都提供了一些易于处理的限制,这些限制导致CQA的可判定性,甚至可处理性。我们还将在关系数据库中将我们的结果与从CQA获得的结果进行比较。

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