Finding data tractable description logics for computing a minimum cost diagnosis based on ABox decomposition

Jianfeng Du, Guilin Qi, Jeff Z. Pan

Research output: Contribution to journalArticlepeer-review

Abstract

Ontology diagnosis, a well-known approach for handling inconsistencies in a description logic (DL) based ontology, computes a diagnosis of the ontology, i.e., a minimal subset of axioms in the ontology whose removal restores consistency. However, ontology diagnosis is computationally hard, especially computing a minimum cost diagnosis (MCD) which is a diagnosis such that the sum of the removal costs attached to its axioms is minimized. This paper addresses this problem by finding data tractable DLs for computing an MCD which allow computing an MCD in time polynomial in the size of the ABox of a given ontology. ABox decomposition is used to find a sufficient and necessary condition to identify data tractable DLs for computing an MCD under the unique name assumption (UNA) among all fragments of SHIN that are at least as expressive as DL — Litecore without inverse roles. The most expressive, data tractable DL identified is SHIN without inverse roles or qualified existential restrictions.
Original languageEnglish
Pages (from-to)623-632
Number of pages10
JournalTsinghua Science and Technology
Volume15
Issue number6
DOIs
Publication statusPublished - 1 Dec 2010

Keywords

  • ontology diagnosis
  • minimum cost diagnosis
  • description logics
  • data tractability

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