Efficiency

HINSCAN: Efficient Structural Graph Clustering over Heterogeneous Information Networks

Structural graph clustering (SCAN) is one of the most popular graph clustering paradigms, and has attracted plenty of attention recently. Existing solutions assume that the input graphs is homogeneous, i.e., the vertices are of the same type. …

Efficient structural node similarity computation on billion-scale graphs (ICDE20 extended to VLDBJ)

Structural node similarity is widely used in analyzing complex networks. As one of the structural node similarity metrics, role similarity has the good merit of indicating automorphism (isomorphism). Existing algorithms to compute role similarity …

StructSim: Querying Structural Node Similarity at Billion Scale

Structural node similarity is widely used in analyzing complex networks. As one of the structural node similarity metrics, role similarity has the good merit of indicating automorphism (isomorphism). Existing algorithms to compute role similarity …