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International Conference on Natural Computation

ICNC 2005: Advances in Natural Computation pp 1170–1178Cite as

Automatic Knowledge Configuration by Reticular Activating System

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3610))

Abstract

Reticular Activating system which has a form of small neural networks in the brain is closely related system with the automatic nervous system. It takes charge of the function that distinguishes between memorizing one and the others, accepts the only selected information and discards the unnecessary things.In this paper, we propose Reticular Activating system which has functions of selective reaction, learning and inference. This system consists of Knowledge acquisition, selection , storing and retrieving part. Reticular Activating layer is connected to Meta knowledge in the high level of this system and takes part in Data Selection. We applied this system to the problem of analyzing the customer’s tastes.

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References

  1. Shim, J.-Y.: Knowledge Retrieval Using Bayesian Associative Relation in the Three Dimensional Modular System. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds.) APWeb 2004. LNCS, vol. 3007, pp. 630–635. Springer, Heidelberg (2004)

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Author information

Authors and Affiliations

  1. Division of General Studies, Computer Science, Kangnam University, San 6-2, Kugal-ri, Kihung-up, YongIn Si, KyeongKi Do, Korea

    JeongYon Shim

Authors
  1. JeongYon Shim
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. School of Software, Sun Yat-Sen University, 510275, Guangzhou, China

    Ke Chen

  3. School of Computer Engineering, Nanyang Technological University, BLK N4, 2b-39, Nanyang Avenue, 639798, Singapore

    Yew Soon Ong

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© 2005 Springer-Verlag Berlin Heidelberg

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Shim, J. (2005). Automatic Knowledge Configuration by Reticular Activating System. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539087_155

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  • DOI: https://doi.org/10.1007/11539087_155

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28323-2

  • Online ISBN: 978-3-540-31853-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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