Abductive Conjunctive Query Answering w.r.t. Ontologies
KI - Künstliche Intelligenz, 30 (2):
177--182 (2016)DOI: doi:10.1007/s13218-015-0399-3
Abstract
In this article we investigate abductive conjunctive query answering w.r.t. ontologies and show how use cases can benefit from this kind of query answering service. While practical reasoning systems such as Racer have supported abductive conjunctive query answering for 10 years now, and many projects have exploited this feature, few publications deal with A-box abduction from an implementation perspective. This article gives a generalized overview on features provided by practical systems and also explains optimization techniques needed to meet practical requirements.