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Tractable Probabilistic Description Logic Programs

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Advances in Probabilistic Databases for Uncertain Information Management

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 304))

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Abstract

We propose tractable probabilistic description logic programs (dl-programs) for the Semantic Web, which combine tractable description logics (DLs), normal programs under the answer set and the well-founded semantics, and probabilities. In detail, we first provide novel reductions of tight query processing and of deciding consistency in probabilistic dl-programs under the answer set semantics to the answer set semantics of the underlying normal dl-programs. Based on these reductions, we then introduce a novel well-founded semantics for probabilistic dl-programs, called the total well-founded semantics. Contrary to the previous answer set and well-founded semantics, it is defined for all probabilistic dl-programs and all probabilistic queries. Furthermore, tight (resp., tight literal) query processing under the total well-founded semantics coincides with (resp., approximates) tight (resp., tight literal) query processing under the previous well-founded (resp., answer set) semantics in all cases where the latter is defined. We then present an anytime algorithm for tight query processing in probabilistic dl-programs under the total well-founded semantics. We also show that tight literal query processing in probabilistic dl-programs under the total well-founded semantics can be done in polynomial time in the data complexity and is complete for EXP in the combined complexity. Finally, we describe an application of probabilistic dl-programs in probabilistic data integration for the Semantic Web.

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  1. Department of Computer Science, University of Oxford, Oxford, UK

    Thomas Lukasiewicz & Gerardo I. Simari

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  1. Thomas Lukasiewicz
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  2. Gerardo I. Simari
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  1. College of Information Science & Engin., Inst. Computer Applications, Northeastern University, Liaoning, Shenyang, 110004, China, People's Republic

    Zongmin Ma

  2. College of Information Science & Engin., School of Software, Northeastern University, Shenyang, 110004, China, People's Republic

    Li Yan

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Lukasiewicz, T., Simari, G.I. (2013). Tractable Probabilistic Description Logic Programs. In: Ma, Z., Yan, L. (eds) Advances in Probabilistic Databases for Uncertain Information Management. Studies in Fuzziness and Soft Computing, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37509-5_6

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