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A Flexible Intelligent Knowledge Capsule for Efficient Data Mining/Reactive Level Extraction

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Affective Computing and Intelligent Interaction (ACII 2005)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3784))

Abstract

The construction of memory and its mechanism is very important to develop the efficient intelligent system. We designed a flexible Intelligent capsule for efficient data mining. The episode memory and its association are specially designed. The proposed knowledge capsule has a hierarchical structure and many functions of selection, learning,storing and data extraction. Based on this knowledge structure, it has a flexible memory and reactive level extraction mechanism. We constructed event oriented virtual memory and tested learning and associative knowledge retrieval function with virtual memory.

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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. National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences,  

    Jianhua Tao

  2. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  3. MIT Media Laboratory, 20 Ames Street, 02139, Cambridge, MA, USA

    Rosalind W. Picard

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© 2005 Springer-Verlag Berlin Heidelberg

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Shim, J. (2005). A Flexible Intelligent Knowledge Capsule for Efficient Data Mining/Reactive Level Extraction. In: Tao, J., Tan, T., Picard, R.W. (eds) Affective Computing and Intelligent Interaction. ACII 2005. Lecture Notes in Computer Science, vol 3784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11573548_112

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  • DOI: https://doi.org/10.1007/11573548_112

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29621-8

  • Online ISBN: 978-3-540-32273-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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