Granular Concept Mapping and Applications

  • Sumalee SonamthiangEmail author
  • Kanlaya Naruedomkul
  • Nick Cercone
Part of the Intelligent Systems Reference Library book series (ISRL, volume 42)


This chapter presents a granular concept hierarchy (GCH) construction and mapping of the hierarchy for granular knowledge. A GCH is comprised of multilevel granular concepts with their hierarchy relations. A rough set based approach is proposed to induce the approximation of a domain concept hierarchy of an information system. A sequence of attribute subsets is selected to partition a granularity, hierarchically. In each level of granulation, reducts and core are applied to retain the specific concepts of a granule whereas common attributes are applied to exclude the common knowledge and generate a more general concept. A granule description language and granule measurements are proposed to enable mapping for an appropriate granular concept that represents sufficient knowledge so solve problem at hand. Applications of GCH are demonstrated through learning of higher order decision rules.


Information granules granular knowledge granular concept hierarchy granular knowledge mapping granule description language higher-order rules multilevel partitioning attribute selection 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sumalee Sonamthiang
    • 1
    Email author
  • Kanlaya Naruedomkul
    • 2
  • Nick Cercone
    • 3
  1. 1.Institute for Innovative LearningMahidol UniversityNakhon PathomThailand
  2. 2.Mathematics Department, Faculty of ScienceMahidol UniversityBangkokThailand
  3. 3.Department of Computer Science and Engineering, Faculty of Science and EngineeringYork UniversityTorontoCanada

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