Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (12): 146-154.doi: 10.11896/jsjkx.211200082

• Database & Big Data & Data Science • Previous Articles     Next Articles

Method of Attributed Heterogeneous Network Embedding with Multiple Features

TANG Qi-you, ZHANG Feng-li, WANG Rui-jin, WANG Xue-ting, ZHOU Zhi-yuan, HAN Ying-jun   

  1. School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China
  • Received:2021-12-07 Revised:2022-03-28 Published:2022-12-14
  • About author:TANG Qi-you,born in 1996,postgra-duate,is a member of China Computer Federation.His main research interests include data mining and network embedding.ZHANG Feng-li,born in 1963,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include network security,cloud computing and big data analysis.
  • Supported by:
    National Natural Science Foundation of China(61802033,61472064,61602096),Sichuan Regional Innovation Cooperation Project(2020YFQ0018),Sichuan Science and Technology Program(2021YFG0027,2020YFG0475,2018GZ0087,2019YJ0543),Chinese Postdoctoral Science Foundation(2018M643453),Guangdong Provincial Key Laboratory Project(2017B030314131) and Network and Data Security Key Laboratory of Sichuan Province Open Issue(NDSMS201606).

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Abstract: Network embedding aims to represent nodes in unstructured network with low-dimensional,real-valued vectors,so that node embedding can retain the structural and attribute features of the original network as much as possible.However,current research mainly focuses on embedding the network structure.There are few researches considering relationship attributes and node attributes with rich semantics in heterogeneous information networks,which mayresult in semetic loss of node embedding and affect the prediction effect of downstream applications.To solve this problem,this paper designs a method of attributed heteroge-neous network embedding with multiple features(MFAHNE).This method integrates the relationship attributes,node attributes and structural semantics in the network into the final node embedding through the steps of sampling sequence,embedding with structural feature,embedding with attribute feature and merging features.Experiment result shows that this method can take into account the structural feature and attribute features,realizes the mutual supplement of two kinds of feature information,and is better than the traditional network embedding methods.

Key words: Network embedding, Heterogeneous information network, Structural feature, Attribute feature, Attributed heterogeneous network

CLC Number: 

  • TP181
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