Preference-Based Inconsistency Assessment in Multi-Context Systems

  • Thomas Eiter
  • Michael Fink
  • Antonius Weinzierl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6341)


Resolving inconsistency in knowledge-integration systems is a major issue, especially when interlinking heterogeneous, autonomous sources. The latter can be done using a multi-context system, also in presence of non-monotonicity. Recent work considered diagnosis and explanation of inconsistency in such systems in terms of faulty information exchange. To discriminate between different solutions, we consider inconsistency assessment using preference. We present means to a) filter undesired diagnoses b) select the most preferred ones given an arbitrary preference order and c) use CP-nets for efficient selection. Furthermore, we show how to incorporate the assessment into a Multi-Context System by a transformational approach. In a range of settings, the complexity does not increase compared to the basic case and key properties like decentralized information exchange and information hiding are preserved.


Inconsistency Management Multi-Context Systems Hybrid Reasoning Systems Nonmonotonic Reasoning Preferences 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Thomas Eiter
    • 1
  • Michael Fink
    • 1
  • Antonius Weinzierl
    • 1
  1. 1.Institute of Information SystemsVienna University of TechnologyViennaAustria

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