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Algorithm Research & Explore
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3252-3257

Integrating active information forwarder of cascade for influence maximization

Yang Shuxin1
Lin Renyao1
Xu Jingfeng1
Liang Wen2
1. School of Information Engineering, Jiangxi University of Science & Technology, Ganzhou Jiangxi 341000, China
2. School of Computer Science & Technology, Changchun University of Science & Technology, Changchun 130000, China

Abstract

The existing works for solving the problem of influence maximization mainly focused on graph and didn't fully exploited the information cascade, which couldn't effectively capture the actual influence between users. To this end, this paper proposed a new approach integrating active information forwarder for influence maximization based on the information cascade. Firstly, this approach designed an embedded neural network model considering active information forwarder and obtained the feature vectors of users by training model supervised by the actual diffusion record of the cascade data. Then, it presented a measurement method of user influence combining the feature vector of active information forwarder and information initiator according to the number of information reachable objects and diffusion probability. Finally, it selected the seeds by using greedy policy. The experimental results with four approaches on three large-scale data sets show the validity of this proposed approach in the actual spread of information.

Foundation Support

国家自然科学基金资助项目(61662028)
江西省教育厅科学技术研究资助项目(GJJ170518)
江西理工大学研究生创新计划资助项目(XY2021-S091)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.04.0186
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 11
Section: Algorithm Research & Explore
Pages: 3252-3257
Serial Number: 1001-3695(2022)11-007-3252-06

Publish History

[2022-06-24] Accepted Paper
[2022-11-05] Printed Article

Cite This Article

杨书新, 林仁耀, 许景峰, 等. 融合级联活跃转发者的社交网络影响最大化方法 [J]. 计算机应用研究, 2022, 39 (11): 3252-3257. (Yang Shuxin, Lin Renyao, Xu Jingfeng, et al. Integrating active information forwarder of cascade for influence maximization [J]. Application Research of Computers, 2022, 39 (11): 3252-3257. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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