Compressing Hypergraphs using Suffix Sorting

Hypergraphs model complex, non-binary relationships such as co-authorships, social group memberships, and recommendation systems. Like traditional graphs, hypergraphs can grow large, posing challenges for storage, transmission, and query performance. We propose HyperCSA, a novel compression method for hypergraphs that maintains support for standard queries over the succinct representation. HyperCSA achieves compression ratios of 26 % to 79 % of the original file size on real-world hypergraphs-outperforming existing methods on all large hypergraphs in our experiments. HyperCSA also scales to larger datasets than existing approaches and evaluates neighbor queries 6 to 40 times faster on common real-world hypergraphs.