A Sparse Stress Model

TL;DR

This paper introduces a faster stress minimization algorithm for graph layouts by aggregating terms in the objective function, improving approximation quality and reducing computation time.

Contribution

It presents a novel aggregation-based speed-up technique for stress models in graph drawing, enhancing efficiency without sacrificing layout quality.

Findings

Achieves better stress layout approximations faster than existing methods.

Uses aggregation of terms to reduce computational complexity.

Experimental results confirm improved performance and quality.

Abstract

Force-directed layout methods constitute the most common approach to draw general graphs. Among them, stress minimization produces layouts of comparatively high quality but also imposes comparatively high computational demands. We propose a speed-up method based on the aggregation of terms in the objective function. It is akin to aggregate repulsion from far-away nodes during spring embedding but transfers the idea from the layout space into a preprocessing phase. An initial experimental study informs a method to select representatives, and subsequent more extensive experiments indicate that our method yields better approximations of minimum-stress layouts in less time than related methods.