发表机构
LIRMM, Inria, University of Montpellier, CNRS; Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI; Inria, DIENS, ENS, PSL University, CNRS（蒙彼利埃大学计算机科学与机器人技术实验室、法国国家信息与自动化研究所、蒙彼利埃大学、法国国家科学研究中心; 波尔多大学、法国国家科学研究中心、波尔多国立综合理工学院、波尔多大学计算机科学实验室; 法国国家信息与自动化研究所、ENS信息与通信科学实验室、巴黎文理研究大学、法国国家科学研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究在由受保护存在规则给出本体的知识库上回答双向正则路径查询的复杂性，针对线性存在规则子类得出数据和组合复杂性结果，对受保护规则归约到线性情况并给出相应复杂性结论。
AI 中文摘要
本体介导的查询回答关注于在由数据库实例和本体组成的知识库上回答查询的问题。虽然该领域的大多数工作集中在合取查询（CQs）上，但导航查询越来越受到关注。本文研究了在本体由一组受保护存在规则给出的知识库上回答双向（合取）正则路径查询（(C)RPQs）的复杂性。我们首先考虑线性存在规则的子类，并表明在数据复杂性方面，(C)RPQ回答是NL完全的，这与在普通图数据库（即没有本体）上回答RPQs的数据复杂性相匹配。在组合复杂性方面，一般情况下这两个任务都是ExpTime完全的，但如果谓词arity有界，RPQ和CRPQ回答分别降至PTime完全和PSpace完全。对于受保护规则，我们提供了一个非平凡的归约到线性情况，这使我们能够表明(C)RPQ回答的复杂性与CQs相同，即在组合复杂性方面是2ExpTime完全的（在有界arity情况下是ExpTime完全的），在数据复杂性方面是PTime完全的。
英文摘要
Ontology-mediated query answering is concerned with the problem of answering queries over knowledge bases consisting of a database instance and an ontology. While most work in the area focuses on conjunctive queries (CQs), navigational queries have gained increasing attention. In this paper, we investigate the complexity of answering two-way (conjunctive) regular path queries ((C)RPQs) over knowledge bases whose ontology is given by a set of guarded existential rules. We first consider the subclass of linear existential rules and show that (C)RPQ answering is NL-complete in data complexity, which matches the data complexity of answering RPQs over plain graph databases (i.e., without an ontology). In combined complexity, both tasks are ExpTime-complete in the general case, but RPQ and CRPQ answering drop to PTime-complete and PSpace-complete respectively if there is a bound on predicate arity. For guarded rules, we provide a non-trivial reduction to the linear case, which allows us to show that the complexity of (C)RPQ answering is the same as for CQs, namely 2ExpTime-complete in combined complexity (ExpTime-complete in the bounded-arity case) and PTime-complete in data complexity.
Comments54 pages. Published version, Journal of Artificial Intelligence Research, Vol. 86, Article 41
Journal refJournal of Artificial Intelligence Research 86, Article 41 (2026), 54 pages
