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System Development & Application
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 5
1441-1445,1453

Link prediction method based on motif evolution in directed dynamic networks

Du Fan
Liu Qun
Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts & Telecommunication, Chongqing 400065, China
DOI: 10.19734/j.issn.1001-3695.2017.11.0738

Abstract

In the past, most of the traditional link prediction methods are oriented to the undirected network, in fact, most social networks are directional, and do not consider the duplication between the same node pair and the microscopic evolution information in the network, therefore they can not solve link prediction in directed dynamic networks better. This paper focused on the directional network, and transformed the repeated edge information between the pair of nodes into the weight of the edge between the pair of nodes, then it used the evolution model based on the triad motif, calculated the motif transformation probability matrix between the adjacent time slice in the move window, analyzed the probability matrix by exponentially weighted moving average, and then it used the matrix to predict the chain edge in the network. This method not only makes full use of the network micro evolution information, but also solves the problem of overlapping edges in dynamic network. Experiments show that this method can get better results than CN, Triad Transition Matrix and other methods in network with high global clustering coefficient and high average degree. Therefore, this method can apply the network microscopic information to the link prediction better.

Foundation Support

国家自然科学基金资助项目(61572091,61075019)
重庆市自然科学基金资助项目(CSTC2014jcyjA40047)
重庆市教委研究项目(KJ1400403)
重庆邮电大学博士启动资助项目(A2014-20)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.11.0738
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: System Development & Application
Pages: 1441-1445,1453
Serial Number: 1001-3695(2019)05-034-1441-05

Publish History

[2019-05-05] Printed Article

Cite This Article

杜凡, 刘群. 有向动态网络中基于模体演化的链路预测方法 [J]. 计算机应用研究, 2019, 36 (5): 1441-1445,1453. (Du Fan, Liu Qun. Link prediction method based on motif evolution in directed dynamic networks [J]. Application Research of Computers, 2019, 36 (5): 1441-1445,1453. )

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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