Community Detection in Random Networks

02/28/2013
by   Ery Arias-Castro, et al.
0

We formalize the problem of detecting a community in a network into testing whether in a given (random) graph there is a subgraph that is unusually dense. We observe an undirected and unweighted graph on N nodes. Under the null hypothesis, the graph is a realization of an Erdös-Rényi graph with probability p0. Under the (composite) alternative, there is a subgraph of n nodes where the probability of connection is p1 > p0. We derive a detection lower bound for detecting such a subgraph in terms of N, n, p0, p1 and exhibit a test that achieves that lower bound. We do this both when p0 is known and unknown. We also consider the problem of testing in polynomial-time. As an aside, we consider the problem of detecting a clique, which is intimately related to the planted clique problem. Our focus in this paper is in the quasi-normal regime where n p0 is either bounded away from zero, or tends to zero slowly.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/13/2013

Community Detection in Sparse Random Networks

We consider the problem of detecting a tight community in a sparse rando...
research
10/02/2021

Random Subgraph Detection Using Queries

The planted densest subgraph detection problem refers to the task of tes...
research
09/07/2019

Community detection in inhomogeneous random graphs

We study the problem of detecting whether an inhomogeneous random graph ...
research
01/15/2021

A practical test for a planted community in heterogeneous networks

One of the fundamental task in graph data mining is to find a planted co...
research
03/06/2023

Localized geometry detection in scale-free random graphs

We consider the problem of detecting whether a power-law inhomogeneous r...
research
03/09/2023

Phase transition for detecting a small community in a large network

How to detect a small community in a large network is an interesting pro...
research
11/13/2019

Searching for Anomalies over Composite Hypotheses

The problem of detecting anomalies in multiple processes is considered. ...

Please sign up or login with your details

Forgot password? Click here to reset