UM
HNS: Hierarchical negative sampling for network representation learning
Chen,Junyang1; Gong,Zhiguo1; Wang,Wei1; Liu,Weiwen2
2021-01-04
Source PublicationInformation Sciences
ISSN0020-0255
Volume542Pages:343-356
AbstractNetwork representation learning (NRL) aims at modeling network graph by encoding vertices and edges into a low-dimensional space. These learned representations can be used for subsequent applications, such as vertex classification and link prediction. Negative Sampling (NS) is the most widely used method for boosting the performance of NRL. However, most of the existing work only randomly draws negative samples based on vertex frequencies, i.e., the vertices with higher frequency are more likely to be drawn, which ignores the situation that the sampled one may not be a true negative sample, thus, lead to undesirable embeddings. In this paper, we propose a new negative sampling method, called Hierarchical Negative Sampling (HNS), which is able to model the latent structures of vertices and learn the relations among them. During sampling, HNS can draw more appropriate negative samples and thereby obtain better performance on network embeddings. Firstly, we theoretically demonstrate the superiority of HNS over NS. And then we use experimental results to show that our proposed method outperforms the state-of-the-art models on vertex classification tasks at different training scales in real-world networks.
KeywordHierarchical negative sampling Network embeddings Network representation learning
DOI10.1016/j.ins.2020.07.015
URLView the original
Language英语
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Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorGong,Zhiguo
Affiliation1.Department of Computer Information Science,University of Macau,Macau,China
2.Department of Computer Science and Engineering,The Chinese University of Hong Kong,Hong Kong
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Chen,Junyang,Gong,Zhiguo,Wang,Wei,et al. HNS: Hierarchical negative sampling for network representation learning[J]. Information Sciences,2021,542:343-356.
APA Chen,Junyang,Gong,Zhiguo,Wang,Wei,&Liu,Weiwen.(2021).HNS: Hierarchical negative sampling for network representation learning.Information Sciences,542,343-356.
MLA Chen,Junyang,et al."HNS: Hierarchical negative sampling for network representation learning".Information Sciences 542(2021):343-356.
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