兰州大学机构库 >信息科学与工程学院
Effective link prediction in multiplex networks: A TOPSIS method
Bai, Shenshen; Zhang, Yakun; Li, LJ(李龙杰); Shan, Na; Chen, XY(陈晓云)
2021-09-01
Source PublicationExpert Systems with Applications
ISSN09574174
Volume177
AbstractThis paper investigates the link prediction in multiplex networks. Multiplex networks that represent multiple types of interaction between the same group of individuals are a special case of complex networks. Each type of interaction is modeled as a layer in a multiplex network. Usually, the topological structures between different layers of a multiplex network have a certain extent of correlation. As a result, the accuracy of link prediction in multiplex networks can be enhanced by combining the information of different layers. In this paper, link prediction in multiplex networks is regarded as a multiple-attribute decision-making problem, in which the potential links in the target layer are considered as alternatives, layers are viewed as attributes, and the similarity score of a potential link in each layer is an attribute value. In implementation, the TOPSIS method is employed to rank alternatives, and interlayer relevance is used to weight the attributes. The experimental results show that the proposed method is not sensitive to the parameter and the interlayer relevance measure, and achieves superior prediction accuracy. © 2021 Elsevier Ltd
KeywordAttribute values Different layers Interlayer relevance Link prediction Multiple attribute decision making problems Multiplex networks Relevance measure Similarity scores Topological structure TOPSIS method Attribute values Different layers Interlayer relevance Link prediction Multiple attribute decision making problems Multiplex networks Relevance measure Similarity scores Topological structure TOPSIS method
PublisherElsevier Ltd
DOI10.1016/j.eswa.2021.114973
Indexed ByEI
Language英语
EI Accession Number20211610223893
EI KeywordsForecasting
EI Classification Number722 Computer Systems and Equipment ; 723 Computer Software, Data Handling and Applications ; 912.2 Management
Original Document TypeJournal article (JA)
Citation statistics
Document Type期刊论文
Identifierhttp://ir.lzu.edu.cn/handle/262010/451271
Collection信息科学与工程学院
AffiliationSchool of Information Science and Engineering, Lanzhou University, Lanzhou; 730000, China
First Author AffilicationSchool of Information Science and Engineering
Recommended Citation
GB/T 7714
Bai, Shenshen,Zhang, Yakun,Li, Longjie,et al. Effective link prediction in multiplex networks: A TOPSIS method[J]. Expert Systems with Applications,2021,177.
APA Bai, Shenshen,Zhang, Yakun,Li, Longjie,Shan, Na,&Chen, Xiaoyun.(2021).Effective link prediction in multiplex networks: A TOPSIS method.Expert Systems with Applications,177.
MLA Bai, Shenshen,et al."Effective link prediction in multiplex networks: A TOPSIS method".Expert Systems with Applications 177(2021).
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