Name
Abstract | ||
|---|---|---|
In this paper, we propose a method of overlapping clustering based on network structure analysis that improves the crisp clustering algorithm proposed by Newman et al. In the proposed technique, we cluster the nodes using Newman's algorithm. We then make a contraction graph in which a cluster is considered as a node. In addition, we cluster the created contraction graph using Newman's clustering algorithm again and identify the overlapping nodes. Overlapping clustering is more flexible than crisp clustering. The experimental results using the real network data and trackback data represented the efficacy of the proposed technique. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/WI-IATW.2007.37 | Wirtschaftsinformatik \/ Angewandte Informatik |
Keywords | Field | DocType |
trackback data,network structure analysis,proposed technique,real network data,overlapping clustering,contraction graph,extraction method,clustering algorithm,overlapping node,crisp clustering algorithm,crisp clustering,graph theory | k-medians clustering,Canopy clustering algorithm,Data mining,Fuzzy clustering,CURE data clustering algorithm,Data stream clustering,Correlation clustering,Computer science,Cluster analysis,Single-linkage clustering | Conference |
ISBN | Citations | PageRank |
0-7695-3028-1 | 5 | 0.46 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Makoto Takaki | 1 | 11 | 2.76 |
| kazuhiro tamura | 2 | 5 | 0.46 |
| Yasuma Mori | 3 | 21 | 9.89 |
| H. Kitakami | 4 | 94 | 49.68 |