Paper Info
Title
DenGraph-HO: a density-based hierarchical graph clustering algorithm
Abstract
AbstractDenGraph-HO is an extension of the density-based graph clustering algorithm DenGraph. It is able to detect dense groups of nodes in a given graph and produces a hierarchy of clusters, which can be efficiently computed. The generated hierarchy can be used to investigate the structure and the characteristics of social networks. Each hierarchy level provides a different level of detail and can be used as the basis for interactive visual social network analysis. After a short introduction of the original DenGraph algorithm, we present DenGraph-HO and its top-down and bottom-up approaches. We describe the data structures and memory requirements and analyse the run-time complexity. Finally, we apply the DenGraph-HO algorithm to the real-world datasets obtained from the online music platform Last.fm and from the former US company Enron.
Year
DOI
Venue
2014
10.1111/exsy.12046
Periodicals
Field
DocType
Volume
Data mining,Social network,Computer science,Theoretical computer science,Artificial intelligence,Clustering coefficient,Hierarchy,Canopy clustering algorithm,Data structure,Level of detail,Social network analysis,Hierarchical clustering of networks,Algorithm,Machine learning
Journal
31
Issue
ISSN
Citations 
5
0266-4720
2
PageRank 
References 
Authors
0.40
19
3
Name
Order
Citations
PageRank
Nico Schlitter181.52
Tanja Falkowski21368.09
Jörg Lässig317522.53