搜索graph attention network共有 14 个结果
1
Document level event extraction based on multi granularity readers and graph attention networks
Accepted Paper
2024年第8期 :
doi:10.19734/j.issn.1001-3695.2024.01.0001
2
Neighborhood information aggregation entity alignment method based on double layer graph attention network
Accepted Paper
2024年第6期 :
doi:10.19734/j.issn.1001-3695.2023.10.0520
3
Knowledge tracing model of temporal and spatial correlation fusion
2024年第5期 : 1381-1387
doi:10.19734/j.issn.1001-3695.2023.09.0414
4
Improved neighborhood search algorithm based on graph neural network
2024年第5期 : 1402-1408
doi:10.19734/j.issn.1001-3695.2023.08.0410
5
TRGATLog:log anomaly detection method based on log time relation graph attention network
2024年第4期 : 1034-1040
doi:10.19734/j.issn.1001-3695.2023.07.0365
6
Blockchain anomaly transaction detection based on GAT and SVM
2024年第1期 : 21-25,31
doi:10.19734/j.issn.1001-3695.2023.05.0207
7
Aspect-level multimodal sentiment analysis based on interaction graph neural network
2023年第12期 : 3683-3689
doi:10.19734/j.issn.1001-3695.2022.10.0532
8
Graph attention-based dual-branch method for social relationship recognition
2023年第11期 : 3315-3320
doi:10.19734/j.issn.1001-3695.2023.03.0102
9
Graph attention network representation learning with node similarity
2023年第3期 : 822-827
doi:10.19734/j.issn.1001-3695.2022.07.0403
10
Crowdsourced task recommendation algorithm based on knowledge graph and graph attention network
2023年第1期 : 115-121
doi:10.19734/j.issn.1001-3695.2022.06.0284
11
Graph attention network based participant recommendation for issue resolution in open source community
2022年第8期 : 2352-2356,2380
doi:10.19734/j.issn.1001-3695.2022.01.0028
12
Joint entity relation extraction based on graph neural network
2022年第2期 : 424-431
doi:10.19734/j.issn.1001-3695.2021.07.0318
13
Entity alignment method based on dual attention and relational semantic modeling
2022年第1期 : 64-69,79
doi:10.19734/j.issn.1001-3695.2021.04.0169
14
Personalized recommendation algorithm based on knowledge graph attention network
2021年第2期 : 398-402
doi:10.19734/j.issn.1001-3695.2020.02.0015