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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2043-2049

Collaborator recommendation model fused academic level similarity

Qin Hongwu
Zhao Meng
Ma Xiuqin
Yan Wenying
College of Computer Science & Engineering, Northwest Normal University, Lanzhou 730070, China
DOI: 10.19734/j.issn.1001-3695.2021.12.0670

Abstract

Collaboration recommendation is helpful to the development of scientific research and the transformation of technological achievements. However, the gap between scholars' academic levels seriously affects the establishment of cooperative relations. This paper made recommendations from three perspectives: the academic level gap between scholars, the topological distance in the collaborative network, and research interests. Firstly, this paper defined three networks, namely scholar-scholar network, scholar-topic network and scholar-level label network, and merged them into a graph of topic-scholar-level label, and set weight to the edges in the graph. Then it turned collaboration recommendation task into a link prediction task. Finally, it employed the biased restart random walk algorithm to calculate the probability of visits among scholars, and recommended the candidate scholars with high visit probability to target scholars. Experiments on three datasets show that the proposed model can improve the precision rate, recall rate and F1 index by 5.4%, 2.7% and 3.8%. In addition, the academic levels of target scholars and recommended scholars are more closely matched.

Foundation Support

国家自然科学基金资助项目(61662067,61662068,61762081)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.12.0670
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Algorithm Research & Explore
Pages: 2043-2049
Serial Number: 1001-3695(2022)07-019-2043-07

Publish History

[2022-02-24] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

秦红武, 赵猛, 马秀琴, 等. 融合学术水平相似性的合作者推荐模型 [J]. 计算机应用研究, 2022, 39 (7): 2043-2049. (Qin Hongwu, Zhao Meng, Ma Xiuqin, et al. Collaborator recommendation model fused academic level similarity [J]. Application Research of Computers, 2022, 39 (7): 2043-2049. )

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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