Effects of "rich-gets-richer" rule on small-world networks

Hongwei Dai; Shangce Gao; Yu Yang; Zheng Tang

doi:10.1016/j.neucom.2010.02.003

Effects of "rich-gets-richer" rule on small-world networks

Hongwei Dai^*, Shangce Gao, Yu Yang, Zheng Tang

^*この論文の責任著者

工学科　知能情報工学コース

研究成果: ジャーナルへの寄稿 › 学術論文 › 査読

8 被引用数 (Scopus)

抄録

In this paper, we propose a new rewiring rule that generates small-world networks with larger clustering coefficient and smaller average path length. Unlike the random rewiring rule in the WS model described by Watts and Strogatz, we use the "rich-gets-richer" rule that links a vertex that already has a large number of connections and has a higher probability. Simulation results also verify that the novel "rich-gets-richer" rule based small-world network is an improvement over the WS model.

本文言語	英語
ページ（範囲）	2286-2289
ページ数	4
ジャーナル	Neurocomputing
巻	73
号	10-12
DOI	https://doi.org/10.1016/j.neucom.2010.02.003
出版ステータス	出版済み - 2010/06

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コンピュータサイエンスの応用
認知神経科学
人工知能

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10.1016/j.neucom.2010.02.003

引用スタイル

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abstract = "In this paper, we propose a new rewiring rule that generates small-world networks with larger clustering coefficient and smaller average path length. Unlike the random rewiring rule in the WS model described by Watts and Strogatz, we use the {"}rich-gets-richer{"} rule that links a vertex that already has a large number of connections and has a higher probability. Simulation results also verify that the novel {"}rich-gets-richer{"} rule based small-world network is an improvement over the WS model.",

keywords = "{"}Rich-gets-richer{"} rule, Average path length, Clustering coefficient, Small-world network",

author = "Hongwei Dai and Shangce Gao and Yu Yang and Zheng Tang",

year = "2010",

month = jun,

doi = "10.1016/j.neucom.2010.02.003",

language = "英語",

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TY - JOUR

T1 - Effects of "rich-gets-richer" rule on small-world networks

AU - Dai, Hongwei

AU - Gao, Shangce

AU - Yang, Yu

AU - Tang, Zheng

PY - 2010/6

Y1 - 2010/6

N2 - In this paper, we propose a new rewiring rule that generates small-world networks with larger clustering coefficient and smaller average path length. Unlike the random rewiring rule in the WS model described by Watts and Strogatz, we use the "rich-gets-richer" rule that links a vertex that already has a large number of connections and has a higher probability. Simulation results also verify that the novel "rich-gets-richer" rule based small-world network is an improvement over the WS model.

AB - In this paper, we propose a new rewiring rule that generates small-world networks with larger clustering coefficient and smaller average path length. Unlike the random rewiring rule in the WS model described by Watts and Strogatz, we use the "rich-gets-richer" rule that links a vertex that already has a large number of connections and has a higher probability. Simulation results also verify that the novel "rich-gets-richer" rule based small-world network is an improvement over the WS model.

KW - "Rich-gets-richer" rule

KW - Average path length

KW - Clustering coefficient

KW - Small-world network

UR - http://www.scopus.com/inward/record.url?scp=77952545313&partnerID=8YFLogxK

U2 - 10.1016/j.neucom.2010.02.003

DO - 10.1016/j.neucom.2010.02.003

M3 - 学術論文

AN - SCOPUS:77952545313

SN - 0925-2312

VL - 73

SP - 2286

EP - 2289

JO - Neurocomputing

JF - Neurocomputing

IS - 10-12

ER -

Effects of "rich-gets-richer" rule on small-world networks

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