Knowledge graphs in the biomedical context are spreading rapidly attracting the strong interest of the research due to their natural way of representing biomedical knowledge by integrating heterogeneous domains (genomic, pharmaceutical, clinical etc.). In this paper we will give an overview of the ...
Mining valuable hidden knowledge from large-scale data relies on the support of reasoning technology. Knowledge graphs, as a new type of knowledge representation, have gained much attention in natural language processing. Knowledge graphs can effectively organize and represent knowledge so that it can ...
概述 Current real-world knowledge graphs are usuallyincompleteand need aninference engineto predict links andcomplete the missing factsamong entities available in the KG. Relation classification or inference from information already available KG is calledlink prediction (链路预测). The process of...
Knowledge Graph Representation Learning Based on Automatic Network Search for Link Prediction Link prediction, also known as Knowledge Graph Completion (KGC), is the common task in Knowledge Graphs (KGs) to predict missing connections between entiti... Zefeng Gu,Hua Chen - CMES-Computer Modeling in...
4.6 RS on Multi-source Heterogeneous Graphs 5. Graph Learning Approaches to RS 5.1 Random Walk Approach 5.2 Graph Representation Learning Approach 5.3 Graph Neural Network Approach 5.4 Knowledge-Graph Approach 6. Open Reseearch Directions 最近在进行推荐系统入门,但是因为事情比较多,读得速度有点慢。这篇...
The application of the knowledge graph, another form of artificial intelligence (AI) in cardiology and cardiovascular medicine, is a new concept, and only... H Wang,Q Zu,M Lu,... - 《Advances in Therapy》 被引量: 0发表: 2022年 A Systematic Literature Review on Personalised Learning in ...
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The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a numb
由深度神经网络驱动的人工智能技术已经在几个应用领域取得了巨大的成功,其中最重要的是在计算机视觉应用程序和自然语言处理任务中。超越人类层面的表现推动了应用领域的研究,其中语言、视觉、感官、文本之间的不同模式在准确预测和识别中发挥着重要作用。在文献中提出了几种采用深度学习模型的多模态融合方法。尽管深度神经...
Microgrids are power distribution systems that can operate either in a grid-connected configuration or in an islanded manner, depending on the availability of decentralized power resources, such as sustainable or non-sustainable power sources, battery backup systems, and power demands. The extensive ado...