Fuzzy graph analysis for sociometry on latticed display

Akira Satoh*, Yoshiyuki Makino, Hajime Yamashita, Hiroshi Suda, Hiroaki Uesu, Kensei Tsuchida

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


The fuzzy graph will make it possible to quantitatively analyze fuzzy information such as expression of human relations and mental processes. To clarify the main feature of a fuzzy graph, we would represent it as an approximate graph and extract its characteristics such as similarity and connectivity structures. Therefore we must proceed to analyze many kinds of information concerning the structure of a fuzzy graph, such as drawing and displaying comprehensively fuzzy graphs in the process. We have developed a computer-aided method for analyzing fuzzy graphs through human interaction. This method can quickly and comprehensively draw a graph arranged on a circular, a partition tree, cluster representative graph corresponding to a cluster and a specified shape of approximate n-valued fuzzy graph. However, it can not draw automatically a graph with nodes on the lattice intersection. So, we would rearrange the nodes on the lattice intersection for any fuzzy graph through user interface. This display is convenient for traditionally analyzing fuzzy graphs. We propose an analysis method using the lattice type of fuzzy graph display. Here, it plays an important role in this system. In this paper, we describe the analysis method and user interface of this system, and their application to sociometry analysis.

Original languageEnglish
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
EditorsM.H. Smith, W.A. Gruver, L.O. Hall
Number of pages6
Publication statusPublished - 2001
EventJoint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC
Duration: 2001 Jul 252001 Jul 28


OtherJoint 9th IFSA World Congress and 20th NAFIPS International Conference
CityVancouver, BC


  • Approximate expression
  • Fuzzy graph
  • Fuzzy model
  • Sociometry analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Media Technology


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