IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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I/E Selective Activation based Knowledge Reconfiguration mechanism and Reasoning

  • Received : 2014.01.15
  • Accepted : 2014.07.28
  • Published : 2014.10.31
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Abstract

As the role of information collection becomes increasingly important in the enormous data environment, there is growing demand for more intelligent information technologies for managing complex data. On the other hand, it is difficult to find a solution because of the data complexity and big scaled amount. Accordingly, there is a need for a special intelligent knowledge base frame that can be operated by itself flexibly. In this paper, by adopting switching function for signal transmission in the synapse of the human brain, I/E selective activation based knowledge reconfiguring mechanism is proposed for building more intelligent information management system. In particular, knowledge network design, a special knowledge node structure, Type definition, I/E gauge definition and I/E matching scheme are provided. Using these concepts, the proposed system makes the functions of activation by I/E Gauge, selection and reconfiguration. In a more efficient manner, the routing and reasoning process was performed based on the knowledge reconfiguration network. In the experiments, the process of selection by I/E matching, knowledge reconfiguration and routing & reasoning results are described.

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References

  1. JeongYon Shim, "Knowledge network Management System with medicine Self Repairing Strategy", PP 119-128, Springer Verlag, Berlin, Heidelberg, 2007.
  2. JeongYon Shim, "Conditional Reconfiguration Mechanism by I/E Gauge", IEEE ISCE2014, The 18th IEEE International Symposium on Consumer Electronics, 22-25 June, Jeju, Korea.
  3. Bruce Goldstein, "Sensation and Perception", Fifth Edition, Brooks/Cole Publishing Company, 1999.
  4. Michael A. Arbib, Jeffrey S. Grethe, "Computing the Brain : A guide to Neuroinformatics", Elsevier Academic Press, 2001.
  5. http://en.wikipedia.org/wiki/Qualia
  6. Thomas M. Cover, Joy A. Thomas, "Elements of Information Theory" Second Edition, Wiley InterScience Press, 2006.
  7. JeongYon Shim, "A Design of Self Internal Entropy Balancing System with Incarnation Process", Vol 4688, LNCS, Springer, 2007.
  8. JeongYon Shim, "Topological Approach of Immunity Based System: Memory Cleaning System", GESTS, 2006.
  9. Olaf Sporns, "Networks of the Brain", The MIT Press, Cambridge, Massachusetts, London, England, Massachusetts Institute of Technology, 2011.
  10. Rita Carter, "Mapping the Memory, - Understanding Your Brain to improve Your memory, The new Neoriscience, Why Mnemonic Tricks Work, A Memory's Synaptic Journey, Keys to Maximizing Memory", Ulysses Press, 2005.
  11. Rex B. Kline, "Principles and Practice of Structural Equation Modeling", Third Edition, The Guilford Press, 2010.
  12. Ning Zhong, Jiming Liu, "Intelligent Technologies for Information Analysis", Springer, 2004. Article (CrossRef Link).
  13. N. Keiding, B.Morgan, T.Speed, P.van der Heijden, "Interdisciplinary Statistics, Generalized Latent Variable Modeling, Multilevel, Longitudinal and Structural Equation Models", Chapman & Hall/CRC, 2004.
  14. Tamraparni Dasu, Theodore Johnson, "Exploratory Data Mining and Data Cleaning, Wiley series in probability and Statistics", Wiley InterScience Press, 2003. Article (CrossRef Link)
  15. Vladimir N. Vapnik, "Statistics for Engineering and Information Science, The Nature of Statistical Learning Theory", Second edition, Springer, 1999.
  16. Rita Carter, "Exploring Consciousness", University of California Press, 2002.
  17. E.Bruce Goldstein, "Sensation and Perception", Fifth Edition, Brooks/Cole Publishing Company, 1999.
  18. Charls T. Meadow, Bert R. Boyce, Donald H. Kraft, Carol Barry, "Text Information Retrieval Systems", Third Edition, Elsevier Academic Press, 2007.
  19. Andrew Ortony, Gerald L. Clore, Allan Collins, "The Cognitive Structure of Emotions", Cambridge University Press, 1994.
  20. Scott L. Miller, Donald G. Childers, "Probability and Random Process, with applications to Signal Processing and Communications", Elsevier Academic Press, 2004.
  21. Carl Edward Rasmussen and Christoper K. I. Williams, "Gaussian Process for Machine Learning", The MIT Press, Massachusetts Institute of Technology, 2006.