Graph compression

Graph compression involves reducing the size of a graph's data structure while preserving its essential information. Think of a graph as a network of nodes (points) connected by edges (lines). Compression identifies patterns and redundancies—such as repeated connections or similar structures—and encodes them efficiently. This process makes storing, transmitting, and analyzing large graphs faster and less resource-intensive without losing important details, similar to how ZIP files compress documents. It's especially useful for handling big data in social networks, biological systems, and transportation maps, ensuring efficient processing while keeping the graph's integrity intact.