Community detection aims at discovering the structure, behavior, dynamics, and
organization of a complex network by finding cohesive groups where nodes (entities) are, in …

Billion-node graphs pose significant challenges at all levels from storage infrastructures to
programming models. It is critical to develop a general purpose platform for graph …

Networks are useful tools to represent and analyze interactions on a large, or genome-wide
scale and have therefore been widely used in biology. Many biological networks—such as …

A recently introduced novel community detection strategy is based on a label propagation
algorithm (LPA) which uses the diffusion of information in the network to identify …

Community detection in networks receives much attention recently. Most of the previous
works are for unipartite networks composed of only one type of nodes. In real world …

A recently introduced novel community detection strategy is based on a label propagation
(LP) algorithm which uses the diffusion of information in the network to identify communities …

Community structure is considered one of the most interesting features in complex networks.
Many real-world complex systems exhibit community structure, where individuals with …

This paper initiates formal analysis of a simple, distributed algorithm for community detection
on networks. We analyze an algorithm that we call Max-LPA, both in terms of its …

Community detection is the fundamental problem in the analysis and understanding of
complex networks, which has attracted a lot of attention in the last decade. Active learning …

This chapter presents the basic label propagation method for network clustering and
partitioning, together with its numerous variants and advances, extensions to different types …