孵化
发表于 2025-3-21 18:57:13
书目名称Database Systems for Advanced Applications影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0263427<br><br> <br><br>书目名称Database Systems for Advanced Applications读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0263427<br><br> <br><br>
摆动
发表于 2025-3-21 23:33:58
https://doi.org/10.1007/978-3-031-30678-5Query Processing; Data Management; Graph; Network; Knowledge Graph
挖掘
发表于 2025-3-22 03:41:56
978-3-031-30677-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
猜忌
发表于 2025-3-22 05:45:24
Christian Masiak,Alexandra Moritz,Frank Langt of the existing approaches can hardly model complicated contexts since they fail to use dependency-type knowledge in texts to assist in identifying implicit clues to event relations, leading to the sub-optimal performance on this task. To this end, we propose a novel type-guided attentive graph co
Mosaic
发表于 2025-3-22 12:31:02
http://reply.papertrans.cn/27/2635/263427/263427_5.png
ENACT
发表于 2025-3-22 13:54:10
Contemporary Ecology Research in Chinaticles into events and connect related events in growing trees to generate storylines. Unfortunately, these methods did not perform well in learning the implicit associations of events. More recently, Graph Convolutional Network (GCN) based methods are proposed to learn the implicit associations bet
ENACT
发表于 2025-3-22 18:13:00
http://reply.papertrans.cn/27/2635/263427/263427_7.png
caldron
发表于 2025-3-22 22:37:47
http://reply.papertrans.cn/27/2635/263427/263427_8.png
小争吵
发表于 2025-3-23 03:10:25
http://reply.papertrans.cn/27/2635/263427/263427_9.png
外露
发表于 2025-3-23 07:56:19
Corporate Ethics and Management Theoryning has been used in UDA, which exploits pseudo-labels for unlabeled target domains. However, the pseudo-labels can be unreliable due to distribution shifts between domains, severely impairing the model performance. To address this problem, we propose a novel self-training framework-Self-Training w