• DocumentCode
    2785539
  • Title

    Knowledge Management Method for Expert System Based on Cognitive Model

  • Author

    Zhu, Shisong ; Kong, Lifang ; Liu, Jinping

  • Volume
    4
  • fYear
    2011
  • fDate
    24-25 Sept. 2011
  • Firstpage
    77
  • Lastpage
    80
  • Abstract
    A living expert system needs a mechanism to update and increase knowledge to adapt this changeable world and the knowledge acquired by different approaches need storage in order for reasoning and updating conveniently. The method presented in this paper bears this mission. Simulating the learning procedure of human beings is the core idea of this method from which we can find the ways how to add, delete, amend and use the knowledge in an expert system. Based on the analysis of the common procedure of children´s actions during recognizing the world, a cognitive model of concept learning is abstracted. A general concept learning algorithm, a knowledge representation method based on general rules, a logical structure in the forest shape, and a uniform data structure for storage are accordingly presented. Thus, a complete and more scientific management case for the knowledge base of expert system is provided. At last, comparing with some ontology knowledge bases, such as CYC, Word Net, and NKI, two different characteristics of this management method are discussed.
  • Keywords
    cognitive systems; expert systems; knowledge management; knowledge representation; cognitive model; concept learning; data structure; expert system; knowledge management; knowledge representation; logical structure; Expert systems; Knowledge management; Knowledge representation; Laser radar; Learning systems; Spread spectrum radar; Cognitive Mode; Concept Learning; Expert System; Knowledge Representation; Knowledge management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on
  • Conference_Location
    Nanjing, Jiangsu
  • Print_ISBN
    978-1-4577-1419-1
  • Type

    conf

  • DOI
    10.1109/ICM.2011.352
  • Filename
    6113695