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JACIII Vol.26 No.1 pp. 17-22
doi: 10.20965/jaciii.2022.p0017
(2022)

Paper:

Improvement of Fuzzy Graph Drawing Using Partition Tree

Yasunori Shiono*, Toshihiro Yoshizumi**, and Kensei Tsuchida***

*Organization for Information Strategy and Promotion, Yokohama National University
79-1 Tokiwadai, Hodogaya, Yokohama, Kanagawa 240-8501, Japan

**Faculty of Management and Economics, Kaetsu University
2-8-4 Minami-cho, Hanakoganei, Kodaira, Tokyo 187-8578, Japan

***Faculty of Information Sciences and Arts, Toyo University
2100 Kujirai, Kawagoe, Saitama 350-8585, Japan

Received:
December 23, 2019
Accepted:
October 8, 2021
Published:
January 20, 2022
Keywords:
fuzzy graph, graph drawing algorithm, cluster analysis
Abstract

Obtaining useful information from ambiguous information is a necessity in various fields. Ambiguous information can be handled quantitatively by using fuzzy theory, and representing it in an easy-to-understand manner is critical. One solution is to visualize an ambiguous relationship by using fuzzy graph representation, which has the essential characteristic of expressing variable relationships in between its nodes. We previously proposed an algorithm to draw intelligible and comprehensive fuzzy graphs. This study describes an improved drawing method for that graph drawing algorithm. As a result, highly related nodes were arranged closer to one another, and the display area was reduced. This method can be used as an effective means of expressing the results of ambiguous information analysis.

Cite this article as:
Yasunori Shiono, Toshihiro Yoshizumi, and Kensei Tsuchida, “Improvement of Fuzzy Graph Drawing Using Partition Tree,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.1, pp. 17-22, 2022.
Data files:
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Last updated on May. 20, 2022