Graph Visualization

Graph visualization aims to represent complex relationships between data points in a visually understandable way, focusing on optimizing layout algorithms to enhance readability and insight extraction. Current research emphasizes developing scalable algorithms, such as those leveraging graph neural networks (GNNs) and stochastic gradient descent, to handle increasingly large datasets and improve the visualization of dynamic graphs. These advancements are crucial for various fields, enabling better analysis of complex systems in areas like smart manufacturing, social network analysis, and document understanding through the effective representation of procedural graphs.