An adaptive discrete particle swarm optimization for influence maximization based on network community structure

doi:10.1142/S0129183119500505

	An adaptive discrete particle swarm optimization for influence maximization based on network community structure
	Tang, Jianxin 1,2; Zhang, Ruisheng 1; Yao, Yabing 2; Zhao, Zhili 1; Chai, Baoqiang 1; Li, Huan 1
刊名	INTERNATIONAL JOURNAL OF MODERN PHYSICS C
	2019-06
卷号	30 期号:6
关键词	Social networks viral marketing influence maximization community detection adaptive discrete particle swarm optimization
ISSN号	0129-1831
DOI	10.1142/S0129183119500505
英文摘要	As an important research field of social network analysis, influence maximization problem is targeted at selecting a small group of influential nodes such that the spread of influence triggered by the seed nodes will be maximum under a given propagation model. It is yet filled with challenging research topics to develop effective and efficient algorithms for the problem especially in large-scale social networks. In this paper, an adaptive discrete particle swarm optimization (ADPSO) is proposed based on network topology for influence maximization in community networks. According to the framework of ADPSO, community structures are detected by label propagation algorithm in the first stage, then dynamic encoding mechanism for particle individuals and discrete evolutionary rules for the swarm are conceived based on network community structure for the meta-heuristic optimization algorithm to identify the allocated number of influential nodes within different communities. To expand the seed nodes reasonably, a local influence preferential strategy is presented to allocate the number of candidate nodes to each community according to its marginal gain. The experimental results on six social networks demonstrate that the proposed ADPSO can achieve comparable influence spread to CELF in an effcient way.
资助项目	National Natural Science Foundations of China[21503101][61702240] ; SRF for ROCS, SEM[[2015] 311] ; Fundamental Research Funds for the Central Universities[lzujbky-2017-191]
WOS研究方向	Computer Science ; Physics
语种	英语
出版者	WORLD SCIENTIFIC PUBL CO PTE LTD
WOS记录号	WOS:000475677000008
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/31823]
专题	计算机与通信学院
通讯作者	Tang, Jianxin
作者单位	1.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
推荐引用方式 GB/T 7714	Tang, Jianxin,Zhang, Ruisheng,Yao, Yabing,et al. An adaptive discrete particle swarm optimization for influence maximization based on network community structure[J]. INTERNATIONAL JOURNAL OF MODERN PHYSICS C,2019,30(6).
APA	Tang, Jianxin,Zhang, Ruisheng,Yao, Yabing,Zhao, Zhili,Chai, Baoqiang,&Li, Huan.(2019).An adaptive discrete particle swarm optimization for influence maximization based on network community structure.INTERNATIONAL JOURNAL OF MODERN PHYSICS C,30(6).
MLA	Tang, Jianxin,et al."An adaptive discrete particle swarm optimization for influence maximization based on network community structure".INTERNATIONAL JOURNAL OF MODERN PHYSICS C 30.6(2019).