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A type-augmented knowledge graph embedding framework for knowledge graph completion
Scientific Reports, 2023 Knowledge graphs (KGs) are of great importance to many artificial intelligence applications, but they usually suffer from the incomplete problem.
Peng He +4 more
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The GeoLink knowledge graph [PDF]
Big Earth Data, 2018 GeoLink has leveraged linked data principles to create a dataset that allows users to seamlessly query and reason over some of the most prominent geoscience metadata repositories in the United States. The GeoLink dataset includes such diverse information
Michelle Cheatham +8 more
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ACM Computing Surveys, 2021 In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data.
Aidan Hogan +17 more
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Advances in Knowledge Graph Embedding Based on Graph Neural Networks [PDF]
Jisuanji kexue yu tansuo, 2023 As graph neural networks continue to develop, knowledge graph embedding methods based on graph neural networks are receiving increasing attention from researchers.
YAN Zhaoyao, DING Cangfeng, MA Lerong, CAO Lu, YOU Hao
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Research and Application Progress of Chinese Medical Knowledge Graph [PDF]
Jisuanji kexue yu tansuo, 2022 Knowledge graph is a large-scale semantic network that gives machine background knowledge. Using knowledge graph to organize heterogeneous medical information can effectively improve the utilization value of massive medical resources and promote the ...
FAN Yuanyuan, LI Zhongmin
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Frontiers in Neurology, 2021 Purpose: Accurate prediction of the progression to severe stroke in initially diagnosed nonsevere patients with acute–subacute anterior circulation nonlacuna ischemic infarction (ASACNLII) is important in making clinical decision.
Lai Wei +15 more
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XR4DRAMA Knowledge Graph: A Knowledge Graph for Media Planning
Proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023 In the previous two decades, knowledge graphs have evolved, inspiring developers to build even more context related Knowledge Graphs. Because of this development, artificial intelligence applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible.
Alexandros Vassiliades +5 more
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Frontiers in Pediatrics, 2021 Leukemia is the most common malignancy affecting children. The morphologic analysis of bone marrow smears is an important initial step for diagnosis. Recent publications demonstrated that artificial intelligence is able to classify blood cells but a long
Min Zhou +23 more
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Towards a biodiversity knowledge graph [PDF]
Research Ideas and Outcomes, 2016 I’ve thrown together some notes on building a biodiversity knowledge graph, and in the interests of making it interactive it's in the form of a web page: http://bionames.org/~rpage/towards-knowledge-graph/. There are buttons to click that display live data, and I hope to dd more examples as I flesh out the ideas.
Roderic Page
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XR4DRAMA Knowledge Graph: A Knowledge Graph for Disaster Management
2023 IEEE 17th International Conference on Semantic Computing (ICSC), 2023 The evolution of Knowledge Graphs (KGs), during the last two decades, has encouraged developers to create more and more context related KGs. This advance is extremely important because Artificial Intelligence (AI) applications can access open domain specific information in a semantically rich, machine understandable format.
Alexandros Vassiliades +6 more
openaire +1 more source