Networks represent relationships between entities in many complex systems, spanning from
online social interactions to biological cell development and brain connectivity. In many …

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 …

In recent years the MapReduce framework has emerged as one of the most widely used
parallel computing platforms for processing data on terabyte and petabyte scales. Used …

In this paper, we describe PEGASUS, an open source peta graph mining library which
performs typical graph mining tasks such as computing the diameter of the graph, computing …

The clustering coefficient of a node in a social network is a fundamental measure that
quantifies how tightly-knit the community is around the node. Its computation can be reduced …

Counting the frequency of small subgraphs is a fundamental technique in network analysis
across various domains, most notably in bioinformatics and social networks. The special …

The core decomposition of networks has attracted significant attention due to its numerous
applications in real-life problems. Simply stated, the core decomposition of a network …

In this paper we propose Fractal, a high performance and high productivity system for
supporting distributed graph pattern mining (GPM) applications. Fractal employs a dynamic …

Triangle counting and enumeration has emerged as a basic tool in large-scale network
analysis, fueling the development of algorithms that scale to massive graphs. Most of the …

This paper presents a new space-efficient algorithm for counting and sampling triangles--
and more generally, constant-sized cliques--in a massive graph whose edges arrive as a …