Physics – Physics and Society
Scientific paper
2008-05-30
Physical Review E78, 046110 (2008)
Physics
Physics and Society
6 pages, 8 figures. Extended version published on Physical Review E. The code to build the new benchmark graphs can be downloa
Scientific paper
10.1103/PhysRevE.78.046110
Community structure is one of the most important features of real networks and reveals the internal organization of the nodes. Many algorithms have been proposed but the crucial issue of testing, i.e. the question of how good an algorithm is, with respect to others, is still open. Standard tests include the analysis of simple artificial graphs with a built-in community structure, that the algorithm has to recover. However, the special graphs adopted in actual tests have a structure that does not reflect the real properties of nodes and communities found in real networks. Here we introduce a new class of benchmark graphs, that account for the heterogeneity in the distributions of node degrees and of community sizes. We use this new benchmark to test two popular methods of community detection, modularity optimization and Potts model clustering. The results show that the new benchmark poses a much more severe test to algorithms than standard benchmarks, revealing limits that may not be apparent at a first analysis.
Fortunato Santo
Lancichinetti Andrea
Radicchi Filippo
No associations
LandOfFree
Benchmark graphs for testing community detection algorithms does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Benchmark graphs for testing community detection algorithms, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Benchmark graphs for testing community detection algorithms will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-318901