Publikation: On Modularity Clustering
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Datum
2008
Autor:innen
Delling, Daniel
Gaertler, Marco
Görke, Robert
Hoefer, Martin
Nikoloski, Zoran
Wagner, Dorothea
Herausgeber:innen
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IEEE Transactions on Knowledge and Data Engineering. 2008, 20(2), pp. 172-188. Available under: doi: 10.1109/TKDE.2007.190689
Zusammenfassung
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 agglomerative approach.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
graph clustering, graph partitioning, modularity, community structure, greedy algorithm
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BRANDES, Ulrik, Daniel DELLING, Marco GAERTLER, Robert GÖRKE, Martin HOEFER, Zoran NIKOLOSKI, Dorothea WAGNER, 2008. On Modularity Clustering. In: IEEE Transactions on Knowledge and Data Engineering. 2008, 20(2), pp. 172-188. Available under: doi: 10.1109/TKDE.2007.190689BibTex
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year={2008},
doi={10.1109/TKDE.2007.190689},
title={On Modularity Clustering},
number={2},
volume={20},
journal={IEEE Transactions on Knowledge and Data Engineering},
pages={172--188},
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