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Community detection, aiming to group nodes based on their connections, plays an important role in network analysis, since communities, treated as meta-nodes, allow us to create a large-scale map of a network to simplify its analysis.
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2019
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A. Bojchevski and S. Günnemann, “Adversarial attacks on node embeddings via graph poisoning,” in International Conference on Machine Learning , 2019, pp. 695–704
2019
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S. Yu, M. Zhao, C. Fu, J. Zheng, H. Huang, X. Shu, Q. Xuan, and G. Chen, “Target defense against link-prediction-based attacks via evolutionary perturbations,” IEEE Transactions on Knowledge and Data Engineering , 2019
2019
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2019
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J. Li, H. Zhang, Z. Han, Y. Rong, H. Cheng, and J. Huang, “Adversarial attack on community detection by hiding individuals,” in Proceedings of The Web Conference 2020 , 2020, pp. 917–927
2020
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