A snapshot cluster segmentation method based on dynamic network

Tongxin Zhang; Luxi Lu

doi:10.1117/12.2656882

13 January 2023 A snapshot cluster segmentation method based on dynamic network

Tongxin Zhang, Luxi Lu

Proceedings Volume 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022); 125101Q (2023) https://doi.org/10.1117/12.2656882
Event: International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 2022, Qingdao, China

Abstract

Dynamic graph neural networks are a research hotspot in the field of deep learning, especially in social networks, recommendation systems, traffic networks and other fields with very wide applications. At present, most of the commonly used deep learning-based network analysis methods are focused on discrete dynamic graph neural networks. However, the effectiveness of discrete graph neural network methods is based on the degree of good or bad snapshot segmentation of dynamic networks, so this paper proposes a Snapshot Clustering Segmentation Method (SCSM) for dynamic networks, and researchers can effectively segment the snapshots of dynamic networks by the SCSM method in this paper to make the downstream tasks can get good results.

Citation Download Citation

Tongxin Zhang and Luxi Lu "A snapshot cluster segmentation method based on dynamic network", Proc. SPIE 12510, International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), 125101Q (13 January 2023); https://doi.org/10.1117/12.2656882

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