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Interval / Probabilistic Uncertainty and Non-Classical Logics pp 87–102Cite as

Label Semantics as a Framework for Granular Modelling

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Part of the book series: Advances in Soft Computing ((AINSC,volume 46))

Summary

An alternative perspective on granular modelling is introduced where an information granule characterises the relationship between a label expression and elements in an underlying perceptual space. Label semantics is proposed as a framework for representing information granules of this kind. Mass relations and linguistic decision trees are then introduced as two types of granular models in label semantics. Finally, its shown how linguistic decision trees can be combined within an attribute hierarchy to model complex multi-level composite mappings.

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Authors and Affiliations

  1. Artificial Intelligence Group, Department of Engineering Mathematics, University of Bristol, BS8 1TR, United Kingdom

    Jonathan Lawry

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  1. Jonathan Lawry
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Editor information

Van-Nam Huynh Yoshiteru Nakamori Hiroakira Ono Jonathan Lawry Vkladik Kreinovich Hung T. Nguyen

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© 2008 Springer-Verlag Berlin Heidelberg

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Lawry, J. (2008). Label Semantics as a Framework for Granular Modelling. In: Huynh, VN., Nakamori, Y., Ono, H., Lawry, J., Kreinovich, V., Nguyen, H.T. (eds) Interval / Probabilistic Uncertainty and Non-Classical Logics. Advances in Soft Computing, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77664-2_8

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  • DOI: https://doi.org/10.1007/978-3-540-77664-2_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77663-5

  • Online ISBN: 978-3-540-77664-2

  • eBook Packages: EngineeringEngineering (R0)

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