NDSU North Dakota State University
Fargo, N.D.

NDSU Institutional Repository

Mining Communities from Multi-Layered Graphs

Show full item record

Click to view higher resolution file
Chao_Mining Communities from Multi-Layered Graphs.pdf
Title: Mining Communities from Multi-Layered Graphs
Author: Chao, Meng
Abstract: Identifying communities from networks has been a subject of great interest in Biological and Social network analysis. Finding communities can help with tasks such as identifying and fighting disease. Using graphs to represent networks and identifying dense subgraphs as communities within these graphs is an increasingly important area of study. Many of the same entities can be found in multiple networks, each representing a different type of relationship. These graphs capturing different relationships between the same entities can be combined into a single graph called a “multi-layered graph”. By finding dense subgraphs containing the same entities within multiple layers of the multi-layered graph, we can increase the confidence these dense subgraphs are communites. This paper has developed an algorithm that takes multi-layered graphs and employs quasi-clique based community discovery for extracting communities. Experimental results on real co-authorship networks show that the proposed approach discover communities that have dense interactions.
Date: -
Subject: Data mining -- Graphic methods.
Social networks -- Data processing.
Computer algorithms.
Permalink: http://hdl.handle.net/10365/23023

This item appears in the following Collection(s)

Show full item record

Search DSpace

Advanced Search


Your Account