兰州大学机构库 >信息科学与工程学院
Link prediction in heterogeneous networks based on metapath projection and aggregation
Zhao, Yuncong1; Sun, Yiyang1; Huang, Yaning2,3; Li, LJ(李龙杰)1,3; Dong, Hu1
2023-10-01
Online publication date2023-05
Source PublicationEXPERT SYSTEMS WITH APPLICATIONS   Impact Factor & Quartile
ISSN0957-4174
Volume227
page numbers8
AbstractA heterogeneous network, which contains multiple types of nodes and edges, is a special kind of network. Link prediction in heterogeneous networks is a consistently interesting research topic owing to its practical value in various applications. In this work, we present an end-to-end link prediction method for heterogeneous networks. By leveraging the metapath projection and semantic graph aggregation, the proposed method can learn the embeddings of node pairs from different metapaths. Specifically, the proposed method projects a heterogeneous network into multiple semantic graphs based on a number of metapaths, and then learns the embedding of a node pair from a probability subgraph extracted in each semantic graph via a graph neural network. Afterward, a semantic aggregation module is designed to combine the embeddings of the node pair obtained from multiple semantic graphs using an attention mechanism. Empirical study manifests that the accuracy of the proposed link prediction method is superior to that of the competing methods. © 2023 Elsevier Ltd
KeywordForecasting Graph embeddings Graph theory Graphic methods Heterogeneous networks Semantics Embeddings Graph neural networks Learn+ Link prediction Metapath Network-based Node pairs Prediction methods Research topics Semantic graphs
PublisherElsevier Ltd
DOI10.1016/j.eswa.2023.120325
Indexed ByEI ; SCIE
Language英语
WOS Research AreaComputer Science ; Engineering ; Operations Research & Management Science
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS IDWOS:001006103600001
EI Accession Number20231914069171
EI KeywordsGraph neural networks
EI Classification Number723.4 Artificial Intelligence ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory
Original Document TypeJournal article (JA) ; Article
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/529641
Collection信息科学与工程学院
Corresponding AuthorLi, Longjie
Affiliation
1.School of Information Science and Engineering, Lanzhou University, Lanzhou; 730000, China;
2.Gansu Daily Group, Lanzhou; 730000, China;
3.Key Laboratory of Media Convergence Technology and Communication, Gansu Province, Lanzhou; 730000, China
First Author AffilicationSchool of Information Science and Engineering
Corresponding Author AffilicationSchool of Information Science and Engineering
Recommended Citation
GB/T 7714
Zhao, Yuncong,Sun, Yiyang,Huang, Yaning,et al. Link prediction in heterogeneous networks based on metapath projection and aggregation[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,227.
APA Zhao, Yuncong,Sun, Yiyang,Huang, Yaning,Li, Longjie,&Dong, Hu.(2023).Link prediction in heterogeneous networks based on metapath projection and aggregation.EXPERT SYSTEMS WITH APPLICATIONS,227.
MLA Zhao, Yuncong,et al."Link prediction in heterogeneous networks based on metapath projection and aggregation".EXPERT SYSTEMS WITH APPLICATIONS 227(2023).
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