2019 AAAI AAAI 2019

Complexity of Inconsistency-Tolerant Query Answering in Datalog+/– under Cardinality-Based Repairs

Abstract

Abstract Querying inconsistent ontological knowledge bases is an important problem in practice, for which several inconsistencytolerant query answering semantics have been proposed, including query answering relative to all repairs, relative to the intersection of repairs, and relative to the intersection of closed repairs. In these semantics, one assumes that the input database is erroneous, and the notion of repair describes a maximally consistent subset of the input database, where different notions of maximality (such as subset and cardinality maximality) are considered. In this paper, we give a precise picture of the computational complexity of inconsistencytolerant (Boolean conjunctive) query answering in a wide range of Datalog± languages under the cardinality-based versions of the above three repair semantics.

🚀 Conference Pioneer — AAAI 2019
🌉 Interdisciplinary Bridge — Artificial Intelligence and Computer Science and Knowledge & Reasoning
🧭 Keyword Pioneer — inconsistency-tolerant semantics
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy