.png){kind=icon}
返回
Special issue on Semantic Deep Learning
.png){kind=icon}
OA
AI
DOI：10.3233/SW-190364.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Numerous success use cases involving deep learning have recently started to be propagated to the Semantic Web. Approaches range from utilizing structured knowledge in the training process of neural networks to enriching such architectures with ontological reasoning mechanisms. Bridging the neural-symbolic gap by joining deep learning and Semantic Web not only holds the potential of improving performance but also of opening up new avenues of research. This editorial introduces the Semantic Web Journal special issue on Semantic Deep Learning, which brings together Semantic Web and deep learning research. After a general introduction to the topic and a brief overview of recent contributions, we continue to introduce the submissions published in this special issue.
Keyword:
Deep learning
Semantic Web
knowledge injection
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.9
论文数:
608
被引数:
1.6K
机构
引用论文
.png){kind=icon}
Sodium channel kinetic changes that produce Brugada syndrome or progressive cardiac conduction system disease产生Brugada综合征或进行性心脏传导系统疾病的钠通道动力学变化
PREAI
分享收藏分享收藏A new approach to a “model-independent” optical potential and its application to proton elastic scattering near the (p,n) threshold energy region一种“模型无关”光学势的新方法及其在近(p,n)阈能区质子弹性散射中的应用
PREAI
分享收藏
查看更多内容