Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its member...
Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Mi...
In this paper we first present a novel approach to determine the structural information content (graph entropy) of a network represented by an undirected and connected graph. Such...
We present an algorithm to compute the cycle structure of large directed graphs where each node has exactly one outgoing edge. Such graphs appear as state diagrams of finite stat...