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Combination methods for identifying influential nodes in networks

Gao, Chao, Zhong, Lu, Li, Xianghua, Zhang, Zili and Shi, Ning 2015, Combination methods for identifying influential nodes in networks, International journal of modern physics c, vol. 26, no. 6, pp. 1-20, doi: 10.1142/S0129183115500679.

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Title Combination methods for identifying influential nodes in networks
Author(s) Gao, Chao
Zhong, Lu
Li, Xianghua
Zhang, ZiliORCID iD for Zhang, Zili orcid.org/0000-0002-8721-9333
Shi, Ning
Journal name International journal of modern physics c
Volume number 26
Issue number 6
Start page 1
End page 20
Total pages 20
Publisher World Scientific Publishing
Place of publication Singapore
Publication date 2015-06
ISSN 0129-1831
Summary Identifying influential nodes is of theoretical significance in many domains. Although lots of methods have been proposed to solve this problem, their evaluations are under single-source attack in scale-free networks. Meanwhile, some researches have speculated that the combinations of some methods may achieve more optimal results. In order to evaluate this speculation and design a universal strategy suitable for different types of networks under the consideration of multi-source attacks, this paper proposes an attribute fusion method with two independent strategies to reveal the correlation of existing ranking methods and indicators. One is based on feature union (FU) and the other is based on feature ranking (FR). Two different propagation models in the fields of recommendation system and network immunization are used to simulate the efficiency of our proposed method. Experimental results show that our method can enlarge information spreading and restrain virus propagation in the application of recommendation system and network immunization in different types of networks under the condition of multi-source attacks.
Language eng
DOI 10.1142/S0129183115500679
Field of Research 01 Mathematical Sciences
02 Physical Sciences
080503 Networking and Communications
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, World Scientific Publishing
Persistent URL http://hdl.handle.net/10536/DRO/DU:30077831

Document type: Journal Article
Collection: School of Information Technology
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