Unsupervised Framework for Evaluating Structural Node Embeddings of Graphs

Author:

Dehghan Ashkan,Siuta Kinga,Skorupka Agata,Betlen Andrei,Miller David,Kamiński Bogumił,Prałat Paweł

Publisher

Springer Nature Switzerland

Reference22 articles.

1. Aggarwal, M., Murty, M.N.: Machine Learning in Social Networks: Embedding Nodes, Edges, Communities, and Graphs. Springer, Singapore (2021). https://doi.org/10.1007/978-981-33-4022-0

2. Ahmed, N.K., et al.: Learning role-based graph embeddings. arXiv preprint arXiv:1802.02896 (2018)

3. Akoglu, L., Tong, H., Koutra, D.: Graph based anomaly detection and description: a survey. Data Min. Knowl. Disc. 29(3), 626–688 (2015)

4. Chami, I., Abu-El-Haija, S., Perozzi, B., Ré, C., Murphy, K.: Machine learning on graphs: a model and comprehensive taxonomy. arXiv preprint arXiv:2005.03675, p. 1 (2020)

5. Dehghan, A., Kamiński, B., Prałat, P.: Node structural representation learning using local signature matrix embedding [LSME] (2022, work in progress)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Surrogate explanations for role discovery on graphs;Applied Network Science;2023-05-26

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