Graph Compression: Toward a Generalized Algorithm

Currently, most graph compression algorithms focus on in-memory compression (such as for web graphs) – few are feasible for external compression, and there is no generalized approach to either task. These compressed representations are versatile and can be applied to a great number of different applications, with the most common being social network and search systems. We present a new set of compression approaches, both lossless and lossy, for external memory graph compression. These new algorithms may also be applicable for runtime usage (i.e., running graph algorithms on the compressed representation).3 pages, 2 figures, 2 tables. https://github.com/danielathome19/GraphCompressio