Signature-Based Abduction for Expressive Description Logics

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Abstract

Signature-based abduction aims at building hypotheses over a specified set of names, the signature, that explain an observation relative to some background knowledge. This type of abduction is useful for tasks such as diagnosis, where the vocabulary used for observed symptoms differs from the vocabulary expected to explain those symptoms. We present the first complete method solving signature-based abduction for observations expressed in the expressive description logic ALC, which can include TBox and ABox axioms. The method is guaranteed to compute a finite and complete set of hypotheses, and is evaluated on a set of realistic knowledge bases.

Bibliographical metadata

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning
EditorsD. Calvanese, E. Erdem
PublisherAI Press
Pages592–602
Number of pages11
DOIs
Publication statusPublished - 12 Sep 2020

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