信息工程大学学报2024，Vol.25Issue(1)：24-29,6.DOI:10.3969/j.issn.1671-0673.2024.01.004
基于动态网络模式变化的网络结构增强嵌入
Network Structure Enhancement Embedding Based on Dynamic Network Pattern Change
张同心 1魏强 2陆路希2
作者信息
- 1. 信息工程大学,河南 郑州 450001||盲信号处理重点实验室,四川 成都 610000
- 2. 盲信号处理重点实验室,四川 成都 610000
- 折叠
摘要
Abstract
Dynamic networks are complex networks as their structures and node features change over time.However,they can better represent the real world,thus attracting the interest of researchers.Although realistic dynamic networks often exhibit changes in their patterns,the existing dynamic network models tend to classify all the snapshots as having the same pattern to learn during their em-bedding.The NS-PCN framework is proposed for this situation,which can extract the pattern infor-mation in the network efficiently according to the change of network patterns.Finally,link prediction experiments are conducted on four real datasets,and the obtained results show a significant improve-ment of the existing dynamic network embedding model in the present framework.关键词
动态网络/网络嵌入/动态图神经网络Key words
dynamic network/network embedding/dynamic graph neural network分类
信息技术与安全科学引用本文复制引用
张同心,魏强,陆路希..基于动态网络模式变化的网络结构增强嵌入[J].信息工程大学学报,2024,25(1):24-29,6.
