Computing subgraph frequencies is a fundamental task that lies at the core of several
network analysis methodologies, such as network motifs and graphlet-based metrics, which …

Counting and enumeration of local topological structures, such as triangles, is an important
task for analyzing large real‐life networks. For instance, triangle count in a network is used …

Roles represent node-level connectivity patterns such as star-center, star-edge nodes, near-
cliques or nodes that act as bridges to different regions of the graph. Intuitively, two nodes …

Graph mining algorithms that aim at identifying structural patterns of graphs are typically
more complex than graph computation algorithms such as breadth first search. Researchers …

Graphlets are induced subgraph patterns and have been frequently applied to characterize
the local topology structures of graphs across various domains, eg, online social networks …

Counting 3-, 4-, and 5-node graphlets in graphs is important for graph mining applications
such as discovering abnormal/evolution patterns in social and biology networks. In addition …

Algorithms for mining very large graphs, such as those representing online social networks,
to discover the relative frequency of small subgraphs within them are of high interest to …

Butterfly counting is an important and costly operation for large bipartite graphs. GPUs are
popular parallel heterogeneous devices and can bring significant performance improvement …

Android systems are widely used in mobile & wireless distributed systems. In the near future,
Android is believed to dominate the mobile distributed environment. However, with the …

Given a large social or information network, how can we partition the vertices into sets (ie,
colors) such that no two vertices linked by an edge are in the same set while minimizing the …