A discrete shuffled frog-leaping algorithm to identify influential nodes for influence maximization in social networks
Tang, Jianxin1,2; Zhang, Ruisheng1; Wang, Ping1; Zhao, Zhili1; Fan, Li1; Liu, Xin1
2020-01
Source PublicationKNOWLEDGE-BASED SYSTEMS
ISSN0950-7051
Volume187
AbstractInfluence maximization problem aims to select a subset of k most influential nodes from a given network such that the spread of influence triggered by the seed set will be maximum. Greedy based algorithm sare time-consuming to approximate the expected influence spread o f given node set accurately and not well scalable to large-scale networks especially when the propagation probability is large. Conventional heuristics based on network topology or confined diffusion paths tend to suffer from the problem of low solution accuracy or huge memory cost. In this paper an effective discrete shuffled frog-leaping algorithm (DSFLA) is proposed to solve influence maximization problem in a more efficient way. Novel encoding mechanism and discrete evolutionary rules are conceived based on network topology structure for virtual frog population. To facilitate the global exploratory solution, a novel local exploitation mechanism combining deterministic and random walk strategies is put forward to improve the suboptimal meme of each memeplex in the frog population. The experimental results of influence spread in six real-world networks and statistical tests show that DSFLA perform s effectively in selecting targeted influential seed nodes for influence maximization and is superior than several state-of-the-art alternatives. (C) 2019 Elsevier B.V. All rights reserved.
KeywordSocial networks Viral marketing Influence maximization Discrete shuffled frog-leaping algorithm Swarm intelligence
DOI10.1016/j.knosys.2019.07.004
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundations of China[21503101][61702240] ; CERNET Innovation Project, China[NGII20170422]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000501653900027
PublisherELSEVIER
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.lut.edu.cn/handle/2XXMBERH/76621
Collection计算机与通信学院
Corresponding AuthorZhang, Ruisheng
Affiliation1.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Gansu, Peoples R China
2.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
First Author AffilicationLanzhou University of Technology
Recommended Citation
GB/T 7714
Tang, Jianxin,Zhang, Ruisheng,Wang, Ping,et al. A discrete shuffled frog-leaping algorithm to identify influential nodes for influence maximization in social networks[J]. KNOWLEDGE-BASED SYSTEMS,2020,187.
APA Tang, Jianxin,Zhang, Ruisheng,Wang, Ping,Zhao, Zhili,Fan, Li,&Liu, Xin.(2020).A discrete shuffled frog-leaping algorithm to identify influential nodes for influence maximization in social networks.KNOWLEDGE-BASED SYSTEMS,187.
MLA Tang, Jianxin,et al."A discrete shuffled frog-leaping algorithm to identify influential nodes for influence maximization in social networks".KNOWLEDGE-BASED SYSTEMS 187(2020).
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