Exploring Evolution of Dynamic Networks via Diachronic Node Embeddings
Exploring Evolution of Dynamic Networks via Diachronic Node Embeddings
复制标题
通过历时节点嵌入探索动态网络的演化
DOI:
10.1109/tvcg.2018.2887230
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发表时间:
2020-07
影响因子:
5.2
通讯作者:
Hai Lin
中科院分区:
文献类型:
--
作者:
Jin Xu;Yubo Tao;Yuyu Yan;Hai Lin
Dynamic networks evolve with their structures changing over time. It is still a challenging problem to efficiently explore the evolution of dynamic networks in terms of both their structural and temporal properties. In this paper, we propose a visual analytics methodology to interactively explore the temporal evolution of dynamic networks in the context of their structure. A novel diachronic node embedding method is first proposed to learn latent representations of the structural and temporal features of nodes in a vector space. Diachronic node embeddings are then used to discover communities with similar structural proximity and temporal evolution patterns. A visual analytics system is designed to enable users to visually explore the evolutions of nodes, communities, and the network as a whole in terms of their structural and temporal properties. We evaluate the effectiveness of our method using artificial and real-world dynamic networks and comparisons with previous methods.
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