Community discovery in complex networks is an interesting problem with a number of
applications, especially in the knowledge extraction task in social and information networks …

Random walk based graph sampling has been recognized as a fundamental technique to
collect uniform node samples from a large graph. In this paper, we first present a …

Our objective is to sample the node set of a large unknown graph via crawling, to accurately
estimate a given metric of interest. We design a random walk on an appropriately defined …

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 …

Causality analysis automates attack forensic and facilitates behavioral detection by
associating causally related but temporally distant system events. Despite its proven …

Exploring statistics of locally connected subgraph patterns (also known as network motifs)
has helped researchers better understand the structure and function of biological and Online …

Online social networks have become a major force in today's society and economy. The
largest of today's social networks may have hundreds of millions to more than a billion users …

Graphs are widely used for representing pairwise interactions in complex systems. Since
such real-world graphs are large and often evergrowing, sampling a small representative …

As online social networking emerges, there has been increased interest to utilize the
underlying network structure as well as the available information on social peers to improve …

Networks are characterized by nodes and edges. While there has been a spate of recent
work on estimating the number of nodes in a network, the edge-estimation question appears …