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    Zhou Liping, Huang Houkuan, Qi Guilin, Qu Youli, Ji Qiu. An Algorithm for Calculating Minimal Unsatisfiability-Preserving Subsets of Ontology in DL-Lite[J]. Journal of Computer Research and Development, 2011, 48(12): 2334-2342.
    Citation: Zhou Liping, Huang Houkuan, Qi Guilin, Qu Youli, Ji Qiu. An Algorithm for Calculating Minimal Unsatisfiability-Preserving Subsets of Ontology in DL-Lite[J]. Journal of Computer Research and Development, 2011, 48(12): 2334-2342.

    An Algorithm for Calculating Minimal Unsatisfiability-Preserving Subsets of Ontology in DL-Lite

    • Inconsistencies occur frequently in ontology lifecycle, such as ontology construction, ontology evolution and ontology merging. Handling inconsistencies, especially, handling logical inconsistency in ontologies is increasingly recognized as an important research topic. Finding all the MUPS (minimal unsatisfiability-preserving sub-TBox) of an ontology for an unsatisfiable concept or role is an important problem because it can provide valuable information for many different tasks of inconsistency handling, such as diagnosing ontology, debugging ontologies and revising ontologies. Many approaches have been proposed to deal with this issue, however, the main drawback of these algorithms is their high computational complexity. One of the main sources of high complexity is the intractability of the underlying description logics (DLs) which may hinder practical applications to very large real life ontologies. In this paper, we focus on DL-Lite, an important tractable description logic which can keep all reasoning tasks tractable and is tailored specifically to deal with large amounts of data. After analyzing some features of unsatisfiable concepts or unsatisfiable roles in DL-Lite, we present an algorithm for computing all MUPS of an ontology for an unsatisfiable concept or role in a DL-Lite ontology. We also present a comparison of our algorithm with another representative algorithm. The results indicate that the proposed algorithm is effecient for real-life DL-Lite ontologies.
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