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  • Probabilistic Reasoning in DL-Lite

    Author(s)
    Ramachandran, R
    Qi, G
    Wang, K
    Wang, J
    Thornton, J
    Griffith University Author(s)
    Thornton, John R.
    Wang, Kewen
    Wang, John
    Qi, Guilin
    Ramachandran, Raghav
    Year published
    2012
    Metadata
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    Abstract
    The problem of extending description logics with uncertainty has received significant attention in recent years. In this paper, we investigate a probabilistic extension of DL-Lite, a family of tractable description logics. We first present a new probabilistic semantics for terminological knowledge bases based on the notion of types. The semantics proposed is not capable of handling assertional knowledge. In order to reason with both terminological and assertional probabilistic knowledge, we propose a probabilistic semantics based on a finite semantics for DL-Lite called features. This approach enables us to infer new ...
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    The problem of extending description logics with uncertainty has received significant attention in recent years. In this paper, we investigate a probabilistic extension of DL-Lite, a family of tractable description logics. We first present a new probabilistic semantics for terminological knowledge bases based on the notion of types. The semantics proposed is not capable of handling assertional knowledge. In order to reason with both terminological and assertional probabilistic knowledge, we propose a probabilistic semantics based on a finite semantics for DL-Lite called features. This approach enables us to infer new information from the existing knowledge base by drawing on the inherent relation between a probabilistic TBox and a probabilistic ABox.
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    Conference Title
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume
    7458 LNAI
    DOI
    https://doi.org/10.1007/978-3-642-32695-0_43
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/48829
    Collection
    • Conference outputs

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