HashWalk: An efficient node classification method based on clique-compressed graph embedding

Shuliang Wang, Xiaorui Qin, Lianhua Chi

Abstract: Highlights•Based on homophily and co-citation hypothesis, cliques reflect structural features of a graph.•Considering a clique as a sample unit improves the quality of random walk.•Compressing graph reduces computational cost in graph embedding.•Compressing graph by consistent cliques preserves structural information.