Title :
On Modularity Clustering
Author :
Brandes, Ulrik ; Delling, Daniel ; Gaertler, Marco ; Görke, Robert ; Hoefer, Martin ; Nikoloski, Zoran ; Wagner, Dorothea
Author_Institution :
Univ. of Konstanz, Konstanz
Abstract :
Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, particularly 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.
Keywords :
graph theory; greedy algorithms; integer programming; linear programming; pattern clustering; graph clustering; greedy agglomerative approach; integer linear programming formulation; modularity clustering; Clustering; Combinatorial algorithms; Computations on discrete structures; G.1.6.a Constrained optimization; Graph Theory; Graphs and networks; Inter programming; Knowledge and data engineering tools and techniques; Mathematics and statistics;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2007.190689