Methods and Applications of Graph Embedding: A Survey

doi:10.3969/j.issn.0372-2112.2020.04.023

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ACTA ELECTRONICA SINICA ›› 2020, Vol. 48 ›› Issue (4) : 808-818. DOI: 10.3969/j.issn.0372-2112.2020.04.023

Methods and Applications of Graph Embedding: A Survey

QI Zhi-wei¹, WANG Jia-hui¹, YUE Kun¹, QIAO Shao-jie², LI Jin³

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Abstract

Graphs are increasingly used in data management, knowledge discovery and information services. As an important strategy of graph analysis and applications, graph embedding has become one of the subjects with great attention in artificial intelligence. Starting from the challenges faced in graph embedding studies, this paper introduces the principal methods based on matrix decomposition, random walk and deep learning. Then, we introduce general test datasets, evaluation criteria as well as typical applications widely used in graph embedding. Finally, we summarize the trend and future research issues of graph embedding.

Key words

graph model / graph embedding method / graph embedding application / test datasets / evaluation metrics

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QI Zhi-wei, WANG Jia-hui, YUE Kun, QIAO Shao-jie, LI Jin. Methods and Applications of Graph Embedding: A Survey[J]. Acta Electronica Sinica, 2020, 48(4): 808-818. https://doi.org/10.3969/j.issn.0372-2112.2020.04.023

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Funding

National Natural Science Foundation of China (No.U1802271, No.61562091, No.61772091, No.61802035); Outstanding Youth Program of Basic Research Project of Yunnan Province (No.2019杰青-2); Applied Basic Research Project of Yunnan Province (No.2016FB110); Scientific Research Fund of Education Department of Yunnan Province (No.2018JS013)