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International Conference on Brain Informatics

BI 2009: Brain Informatics pp 115–126Cite as

Structured Prior Knowledge and Granular Structures

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5819))

Abstract

In this paper, a hierarchical organization of prior knowledge based on multidimensional data model is firstly proposed, it is the basis of structured thinking. Secondly, a representation of granular structures based on multidimensional data model is also proposed, it can represents information from multiview and multilevel. Finally, the relation between structured prior knowledge and granular structures is analyzed.

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Author information

Authors and Affiliations

  1. School of Mathematics and Computer Science, Shanxi Normal University, Linfen, Shanxi, 041004, P.R. China

    Qinrong Feng

  2. Department of Computer Science and Technology, Tongji University, Shanghai, 201804, P.R. China

    Qinrong Feng & Duoqian Miao

Authors
  1. Qinrong Feng
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  2. Duoqian Miao
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Editor information

Editors and Affiliations

  1. Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, 371.0816, Maebashi-City, Japan

    Ning Zhong

  2. Department of Radiology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, People’s Republic of China

    Kuncheng Li

  3. The International WIC Institute, Beijing University of Technology, China

    Shengfu Lu

  4. Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Chaoyng District, 100101, Beijing, China

    Lin Chen

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© 2009 Springer-Verlag Berlin Heidelberg

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Cite this paper

Feng, Q., Miao, D. (2009). Structured Prior Knowledge and Granular Structures. In: Zhong, N., Li, K., Lu, S., Chen, L. (eds) Brain Informatics. BI 2009. Lecture Notes in Computer Science(), vol 5819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04954-5_22

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  • DOI: https://doi.org/10.1007/978-3-642-04954-5_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04953-8

  • Online ISBN: 978-3-642-04954-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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