An Empirical Evaluation of Force-Directed Graph Layout

<p>Force-directed graph layout is a widely used algorithm for the automatic layout of graphs. Little experimental work has been done exploring the behaviour of the algorithm under a variety of conditions. This thesis carries out three large-scale metric-based experiments. The first explores how the core algorithm behaves under changes to initial conditions. The second looks at extending the force-directed layout algorithm with additional forces to reduce overlaps. The third develops a novel symmetry metric for graphs and uses that to explore the symmetries of graphs. This thesis also carries out a user study to show that the differences reported by metrics in the graphs are reflected in a difference in user performance when using graphs for a free-form selection task.</p>

An Empirical Evaluation of Force-Directed Graph Layout

<p>Force-directed graph layout is a widely used algorithm for the automatic layout of graphs. Little experimental work has been done exploring the behaviour of the algorithm under a variety of conditions. This thesis carries out three large-scale metric-based experiments. The first explores how the core algorithm behaves under changes to initial conditions. The second looks at extending the force-directed layout algorithm with additional forces to reduce overlaps. The third develops a novel symmetry metric for graphs and uses that to explore the symmetries of graphs. This thesis also carries out a user study to show that the differences reported by metrics in the graphs are reflected in a difference in user performance when using graphs for a free-form selection task.</p>

Graphs from Features: Tree-Based Graph Layout for Feature Analysis

Feature Analysis has become a very critical task in data analysis and visualization. Graph structures are very flexible in terms of representation and may encode important information on features but are challenging in regards to layout being adequate for analysis tasks. In this study, we propose and develop similarity-based graph layouts with the purpose of locating relevant patterns in sets of features, thus supporting feature analysis and selection. We apply a tree layout in the first step of the strategy, to accomplish node placement and overview based on feature similarity. By drawing the remainder of the graph edges on demand, further grouping and relationships among features are revealed. We evaluate those groups and relationships in terms of their effectiveness in exploring feature sets for data analysis. Correlation of features with a target categorical attribute and feature ranking are added to support the task. Multidimensional projections are employed to plot the dataset based on selected attributes to reveal the effectiveness of the feature set. Our results have shown that the tree-graph layout framework allows for a number of observations that are very important in user-centric feature selection, and not easy to observe by any other available tool. They provide a way of finding relevant and irrelevant features, spurious sets of noisy features, groups of similar features, and opposite features, all of which are essential tasks in different scenarios of data analysis. Case studies in application areas centered on documents, images and sound data demonstrate the ability of the framework to quickly reach a satisfactory compact representation from a larger feature set.

Study of model problem of structural bioinformatics

The paper is devoted to the study of methods for solving problems of structural bioinformatics on the example of solving a model problem of graphs layout on a plane. The paper considers an "energy" approach to solving this type of problems, based on the use of continuous optimization methods, the purpose of which is to find a configuration with a minimum energy. The paper formulates a model problem of graph layout, describes the structure of graphs to be processed, and defines an objective function that simulates the internal energy of graph layout. Several popular optimization methods are described, including a genetic algorithm and a differential evolution algorithm. Parallel variations of these two algorithms are considered. Implementation of a software system for automatic testing of a user-defined algorithm for solving model folding problems with support for parallel computing, web interface and visualization of computations is described. The work was carried out with the financial support of the Russian Foundation for Basic Research (Grant No. 20-07-01053 A).