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On Modularity Clustering
February 2008 (vol. 20 no. 2)
pp. 172-188
ASCII Text
x 
 
Ulrik Brandes, Daniel Delling, Marco Gaertler, Robert G?rke, Martin Hoefer, Zoran Nikoloski, Dorothea Wagner, "On Modularity Clustering," IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 2, pp. 172-188, February, 2008.
 
 
BibTex
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@article{ 10.1109/TKDE.2007.190689,
author = {Ulrik Brandes and Daniel Delling and Marco Gaertler and Robert G?rke and Martin Hoefer and Zoran Nikoloski and Dorothea Wagner},
title = {On Modularity Clustering},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {20},
number = {2},
issn = {1041-4347},
year = {2008},
pages = {172-188},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2007.190689},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - On Modularity Clustering
IS - 2
SN - 1041-4347
SP172
EP188
EPD - 172-188
A1 - Ulrik Brandes,
A1 - Daniel Delling,
A1 - Marco Gaertler,
A1 - Robert G?rke,
A1 - Martin Hoefer,
A1 - Zoran Nikoloski,
A1 - Dorothea Wagner,
PY - 2008
KW - Computations on discrete structures
KW - Knowledge and data engineering tools and techniques
KW - Graphs and networks
KW - Inter programming
KW - G.1.6.a Constrained optimization
KW - Combinatorial algorithms
KW - Graph Theory
KW - Clustering
KW - Clustering
KW - Mathematics and statistics
VL - 20
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 
Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, and in particular in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts, and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomaration approach.

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Index Terms:
Computations on discrete structures, Knowledge and data engineering tools and techniques, Graphs and networks, Inter programming, G.1.6.a Constrained optimization, Combinatorial algorithms, Graph Theory, Clustering, Clustering, Mathematics and statistics
Citation:
Ulrik Brandes, Daniel Delling, Marco Gaertler, Robert G?rke, Martin Hoefer, Zoran Nikoloski, Dorothea Wagner, "On Modularity Clustering," IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 2, pp. 172-188, Feb. 2008, doi:10.1109/TKDE.2007.190689
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