Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 6
1647-1651

Clustering-preserving representation learning on attributed network

Zhang Jinga
Chai Bianfanga
Zhang Pua
Li Wenbinb
a. School of Information Engineering, b. Academic Affairs Office, Hebei Geo University, Shijiazhuang 050031, China
DOI: 10.19734/j.issn.1001-3695.2018.12.0879

Abstract

The online social platform generates a lot of data that can be modeled as attributed network. The representation learning model of SNE(social network embedding) can learn the potential low-dimensional representation of the attributed network, which provides effective features for further practical applications. However, SNE does not consider preserving the potential clustering structure of the network, which results in bad clustering effect. In order to solve these problems, this paper proposed an attributed network representation learning model(attributed network embedding with self cluster, ANESC) that preserved the clustering structure, which used feedforward neural network to model. ANESC took one-hot representation and attributed information of attributed network nodes as input, with multi-hidden layer learning node′s low-dimensional representation, it preserved the node's neighbor topology and potential clustering structure at the output layer. The empirical results of five real attributed networks show that compared with the presentation that SNE learns, the NMI value of presentation that ANESC learns in clustering task increases by 5%~11%, and the accuracy of classification increases by 0.3%~7%.

Foundation Support

国家自然科学基金资助项目(61503260)
河北省研究生创新资助项目(CXZZSS2018118)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.12.0879
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 6
Section: Algorithm Research & Explore
Pages: 1647-1651
Serial Number: 1001-3695(2020)06-008-1647-05

Publish History

[2020-06-05] Printed Article

Cite This Article

张静, 柴变芳, 张璞, 等. 保持聚类结构的属性网络表示学习 [J]. 计算机应用研究, 2020, 37 (6): 1647-1651. (Zhang Jing, Chai Bianfang, Zhang Pu, et al. Clustering-preserving representation learning on attributed network [J]. Application Research of Computers, 2020, 37 (6): 1647-1651. )

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  • Application Research of Computers Monthly Journal
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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.

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