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On Partial Features in the \(\mathcal{DLF}\) Family of Description Logics

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PRICAI 2016: Trends in Artificial Intelligence (PRICAI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9810))

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Abstract

The \(\mathcal{DLF}\) family of description logics are fragments of first order logic with underlying signatures based on unary predicate symbols, called atomic concepts, and unary function symbols interpreted as total functions, called features. We show how computational properties relating to a key reasoning service for dialects of this family are preserved when (a) unary function symbols are now interpreted as partial functions, and when (b) a concept constructor is admitted that can characterize circumstances in which partial functions become total.

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Notes

  1. 1.

    Such issues can be (and we believe should be) explicitly addressed elsewhere in an ontology.

  2. 2.

    This arrangement is common and is referred to as the strict interpretation of undefined values.

  3. 3.

    The last rule in the figure does not apply to \({ partial\!-\! \mathcal{{CFD}}}\) and is added w.l.o.g. in preparation for treating \({partial\!-\!}{{\mathcal {CFD}}}^{\forall }_{nc}\). This rule is neither necessary nor applicable in the \({ partial\!-\! \mathcal{{CFD}}}\) case.

  4. 4.

    The details for this are beyond the scope of the paper.

References

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Author information

Authors and Affiliations

  1. Cheriton School of Computer Science, University of Waterloo, Waterloo, Canada

    David Toman & Grant Weddell

Authors
  1. David Toman
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  2. Grant Weddell
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Corresponding author

Correspondence to David Toman .

Editor information

Editors and Affiliations

  1. Cardiff University, Cardiff, United Kingdom

    Richard Booth

  2. Southeast University , Nanjing, China

    Min-Ling Zhang

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Toman, D., Weddell, G. (2016). On Partial Features in the \(\mathcal{DLF}\) Family of Description Logics. In: Booth, R., Zhang, ML. (eds) PRICAI 2016: Trends in Artificial Intelligence. PRICAI 2016. Lecture Notes in Computer Science(), vol 9810. Springer, Cham. https://doi.org/10.1007/978-3-319-42911-3_44

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  • DOI: https://doi.org/10.1007/978-3-319-42911-3_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42910-6

  • Online ISBN: 978-3-319-42911-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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