With the advent of a wide spectrum of recent applications, querying heterogeneous
information networks (HINs) has received a great deal of attention from both academic and …

We present a parallel k-clique listing algorithm with improved work bounds (for the same
depth) in sparse graphs with low degeneracy or arboricity. We achieve this by introducing …

Higher-order graph clustering aims to partition the graph using frequently occurring
subgraphs (ie, motifs), instead of the lower-order edges, as the atomic clustering unit, which …

With the prevalence of graphs for modeling complex relationships among objects, the topic
of graph mining has attracted a great deal of attention from both academic and industrial …

We present a GPU solution for exact maximal clique enumeration (MCE) that performs a
search tree traversal following the Bron-Kerbosch algorithm. Prior works on parallelizing …

Listing all k-cliques is a fundamental problem in graph mining, with applications in finance,
biology, and social network analysis. However, owing to the exponential growth of the …

Counting k-cliques in a graph is an important problem in graph analysis with many
applications such as community detection and graph partitioning. Counting k-cliques is …

Conductance-based graph clustering has been recognized as a fundamental operator in
numerous graph analysis applications. Despite the significant success of conductance …

K-clique counting is a fundamental problem in network analysis which has attracted much
attention in recent years. Computing the count of k-cliques in a graph for a large k (eg, k= 8) …

k-defective cliques relax cliques by allowing up-to k missing edges from being a complete
graph. This relaxation enables us to find larger near-cliques and has applications in link …