| CHEN Jing (陈晶)* ****,QI Ziyi* ** ***,LIU Mingxin****.[J].高技术通讯(英文),2022,28(2):153~163 |
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| Time sequential influence maximization algorithm based on neighbor node influence |
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| DOI：10.3772/j.issn.1006-6748.2022.02.005 |
| 中文关键词: |
| 英文关键词: neighbor node influence, time sequential social network, influence maximization (IM), information propagation model |
| 基金项目: |
| Author Name | Affiliation | | CHEN Jing (陈晶)* **** | (*School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, P.R.China)
(**Hebei Key Laboratory of Virtual Technology and System Integration, Qinhuangdao 066004, P.R.China)
(***Hebei Key Laboratory of Software Engineering, Qinhuangdao 066004, P.R.China)
(****College of Electronic and Information Engineering,Guangdong Ocean University, Zhanjiang 524088, P.R.China) | | QI Ziyi* ** *** | (*School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, P.R.China)
(**Hebei Key Laboratory of Virtual Technology and System Integration, Qinhuangdao 066004, P.R.China)
(***Hebei Key Laboratory of Software Engineering, Qinhuangdao 066004, P.R.China)
(****College of Electronic and Information Engineering,Guangdong Ocean University, Zhanjiang 524088, P.R.China) | | LIU Mingxin**** | (*School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, P.R.China)
(**Hebei Key Laboratory of Virtual Technology and System Integration, Qinhuangdao 066004, P.R.China)
(***Hebei Key Laboratory of Software Engineering, Qinhuangdao 066004, P.R.China)
(****College of Electronic and Information Engineering,Guangdong Ocean University, Zhanjiang 524088, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| In view of the forwarding microblogging, secondhand smoke, happiness, and many other phenomena in real life, the spread characteristic of the secondary neighbor nodes in this kind of phenomenon and network scheduling is extracted, and sequence influence maximization problem based on the influence of neighbor nodes is proposed in this paper. That is, in the time sequential social network, the propagation characteristics of the second-level neighbor nodes are considered emphatically, and k nodes are found to maximize the information propagation. Firstly, the propagation probability between nodes is calculated by the improved degree estimation algorithm. Secondly, the weighted cascade model (WCM) based on static social network is not suitable for temporal social network. Therefore, an improved weighted cascade model (IWCM) is proposed, and a second-level neighbors time sequential maximizing influence algorithm (STIM) is put forward based on node degree. It combines the consideration of neighbor nodes and the problem of overlap of influence scope between nodes, and makes it chronological. Finally, the experiment verifies that STIM algorithm has stronger practicability, superiority in influence range and running time compared with similar algorithms, and is able to solve the problem of maximizing the timing influence based on the influence of neighbor nodes. |
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