Name
Abstract | ||
|---|---|---|
We use the k-core decomposition to develop algorithms for the analysis of large scale complex networks. This decomposition, based on a re- cursive pruning of the least connected vertices, allows to disentangle the hierarchical structure of networks by progressively focusing on their cen- tral cores. By using this strategy we develop a general visualization algo- rithm that can be used to compare the structural properties of various net- works and highlight their hierarchical structure. The low computational complexity of the algorithm,O(n + e), where n is the size of the net- work, ande is the number of edges, makes it suitable for the visualization of very large sparse networks. We show how the proposed visualization tool allows to find specific structural fingerprints of networks. |
Year | Venue | Keywords |
|---|---|---|
2005 | NIPS | computational complexity,complex network |
Field | DocType | Citations |
Vertex (geometry),Computer science,Central cores,Visualization,Hierarchical network model,Artificial intelligence,Complex network,Recursion,Machine learning,Computational complexity theory,Decomposition | Conference | 83 |
PageRank | References | Authors |
5.50 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Ignacio Alvarez-hamelin | 1 | 143 | 13.31 |
| Luca Dall'Asta | 2 | 493 | 39.53 |
| Alain Barrat | 3 | 1401 | 87.12 |
| Alessandro Vespignani | 4 | 1647 | 109.55 |