Maximizing the spread of influence via the collective intelligence of discrete bat algorithm

doi:10.1016/j.knosys.2018.06.013

	Maximizing the spread of influence via the collective intelligence of discrete bat algorithm
	Tang, Jianxin 1,2; Zhang, Ruisheng 1; Yao, Yabing 1; Zhao, Zhili 1; Wang, Ping 1; Li, Huan 1; Yuan, Jinliang 1
刊名	KNOWLEDGE-BASED SYSTEMS
	2018-11-15
卷号	160 页码:88-103
关键词	Social network Influence maximization Metaheuristic Discrete bat algorithm Collective intelligence
ISSN号	0950-7051
DOI	10.1016/j.knosys.2018.06.013
英文摘要	Influence maximization aims to select a small set of k influential nodes to maximize the spread of influence. It is still an open research topic to develop effective and efficient algorithms for the optimization problem. Greedy-based algorithms utilize the property of "submodularity" to provide performance guarantee, but the computational cost is unbearable especially in large-scale networks. Meanwhile, conventional topology-based centrality methods always fail to provide satisfying identification of influential nodes. To identify the k influential nodes effectively, we propose a metaheuristic discrete bat algorithm (DBA) based on the collective intelligence of bat population in this paper. According to the evolutionary rules of the original bat algorithm (BA), a probabilistic greedy-based local search strategy based on network topology is presented and a CandidatesPool is generated according to the contribution of each node to the network topology to enhance the exploitation operation of DBA. The experimental results and statistic tests on five real-world social networks and a synthetic network under independent cascade model demonstrate that DBA outperforms other two metaheuristics and the Stop-and-Stair algorithm, and achieves competitive influence spread to CELF (Cost-Effective Lazy Forward) but has less time computation than CELF.
资助项目	Fundamental Research Funds for the Central Universities[lzujbky-2017-191]
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000446283900008
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/32337]
专题	计算机与通信学院
通讯作者	Zhang, Ruisheng
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. Maximizing the spread of influence via the collective intelligence of discrete bat algorithm[J]. KNOWLEDGE-BASED SYSTEMS,2018,160:88-103.
APA	Tang, Jianxin.,Zhang, Ruisheng.,Yao, Yabing.,Zhao, Zhili.,Wang, Ping.,...&Yuan, Jinliang.(2018).Maximizing the spread of influence via the collective intelligence of discrete bat algorithm.KNOWLEDGE-BASED SYSTEMS,160,88-103.
MLA	Tang, Jianxin,et al."Maximizing the spread of influence via the collective intelligence of discrete bat algorithm".KNOWLEDGE-BASED SYSTEMS 160(2018):88-103.