A Framework for Building Intelligent Information-Processing Systems Based on Granular Factors Space

  • Fusheng Yu
  • Chongfu Huang
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 95)


Reviewing the current Artificial Intelligent (AI) techniques of knowledge representation, knowledge acquisition and inference, in this chapter, we develop the factors space into the granular factors space for building intelligent information-processing systems. In details, we discuss, using the factors space methods and granular factors space methods, how to represent knowledge — concepts(in extension and intention), facts, and rules, how to acquire refined knowledge from source knowledge automatically, and how to reason with explaining property quickly. To facilitate our studying, a tool for building diagnostic expert systems is provided.


Knowledge Representation Inference Method Factor Space Fuzzy Relation Characteristic Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Fusheng Yu
    • 1
  • Chongfu Huang
    • 2
    • 3
  1. 1.Department of MathematicsBeijing Normal UniversityBeijingChina
  2. 2.Institute of Resources ScienceBeijing Normal UniversityBeijingChina
  3. 3.Key Laboratory of Environmental Change and Natural DisasterThe Ministry of Education of ChinaChina

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