Source:http://linkedlifedata.com/resource/pubmed/id/16383501
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4 Pt 2
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| pubmed:dateCreated |
2005-12-30
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| pubmed:abstractText |
For most networks, the connection between two nodes is the result of their mutual affinity and attachment. In this paper, we propose a mutual selection model to characterize the weighted networks. By introducing a general mechanism of mutual selection, the model can produce power-law distributions of degree, weight, and strength, as confirmed in many real networks. Moreover, we also obtained the nontrivial clustering coefficient C, degree assortativity coefficient r, and degree-strength correlation depending on a single parameter m. These results are supported by present empirical evidence. Studying the degree-dependent average clustering coefficient C(k) and the degree-dependent average nearest neighbors' degree k(nn)(k) also provide us with a better description of the hierarchies and organizational architecture of weighted networks.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:month |
Oct
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| pubmed:issn |
1539-3755
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
72
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
046140
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| pubmed:year |
2005
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| pubmed:articleTitle |
Mutual selection model for weighted networks.
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| pubmed:affiliation |
Nonlinear Science Center and Department of Modern Physics, University of Science and Technology of China, Hefei, 230026, People's Republic of China.
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| pubmed:publicationType |
Journal Article
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