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Self-Organizing Map with Input Data Represented as Graph

  • Conference paper
Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4232))

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Abstract

This paper proposes a new method of Self-Organizing Map (SOM) in which an input space is represented as a graph by modifications of a distance measure and a updating rule. The distance between input node and reference element is defined by the shortest distance between them in the graph. The reference elements are updated along the shortest path to the input node. The effectiveness of the proposed method is verified by applying it to a Traveling Salesman Problem.

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Author information

Authors and Affiliations

  1. Graduate school of Life Science and Systems Engineering, Kyushu Institute of Technology, Hibikino, Wakamatsu, Kitakyushu, Fukuoka, 808-0196, Japan

    Takeshi Yamakawa & Keiichi Horio

  2. Ricoh Co., Ltd,  

    Masaharu Hoshino

Authors
  1. Takeshi Yamakawa
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  2. Keiichi Horio
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  3. Masaharu Hoshino
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, The Chinese Univ. of Hong Kong, Shatin, N.T., Hong Kong

    Irwin King

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Lai-Wan Chan

  4. Department of Computer Science and Engineering & Center for Cognitive Science, The Ohio State University, OH 43210, Columbus

    DeLiang Wang

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Yamakawa, T., Horio, K., Hoshino, M. (2006). Self-Organizing Map with Input Data Represented as Graph. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893028_101

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  • DOI: https://doi.org/10.1007/11893028_101

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46479-2

  • Online ISBN: 978-3-540-46480-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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