Graphs Drawing through Fuzzy Clustering

TL;DR

This paper explores advanced graph drawing techniques using force-directed algorithms combined with fuzzy clustering to improve visualization quality and overcome local minima in the optimization process.

Contribution

It introduces a novel multi-surface approach based on fuzzy clustering algorithms to enhance force-directed graph drawing methods.

Findings

Fuzzy clustering improves graph layout optimization.

Multi-surface approach reduces local minima issues.

Enhanced visualization of undirected graphs.

Abstract

Many problems can be presented in an abstract form through a wide range of binary objects and relations which are defined over problem domain. In these problems, graphical demonstration of defined binary objects and solutions is the most suitable representation approach. In this regard, graph drawing problem discusses the methods for transforming combinatorial graphs to geometrical drawings in order to visualize them. This paper studies the force-directed algorithms and multi-surface techniques for drawing general undirected graphs. Particularly, this research describes force-directed approach to model the drawing of a general graph as a numerical optimization problem. So, it can use rich knowledge which is presented as an established system by the numerical optimization. Moreover, this research proposes the multi-surface approach as an efficient tool for overcoming local minimums in standard force-directed algorithms. Next, we introduce a new method for multi-surface approach based on fuzzy clustering algorithms.