2018 IJCAI IJCAI 2018

Complexity of Approximate Query Answering under Inconsistency in Datalog+/-

Abstract

Several semantics have been proposed to query inconsistent ontological knowledge bases, including the intersection of repairs and the intersection of closed repairs as two approximate inconsistency-tolerant semantics. In this paper, we analyze the complexity of conjunctive query answering under these two semantics for a wide range of Datalog+/- languages. We consider both the standard setting, where errors may only be in the database, and the generalized setting, where also the rules of a Datalog+/- knowledge base may be erroneous.

🧭 Keyword Pioneer — repair semantics
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio