Results 21 to 30 of about 7,444,582 (260)
Scientific Reports, 2021 This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19.
Feng Pan +10 more
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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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Text-Graph Enhanced Knowledge Graph Representation Learning
Frontiers in Artificial Intelligence, 2021 Knowledge Graphs (KGs) such as Freebase and YAGO have been widely adopted in a variety of NLP tasks. Representation learning of Knowledge Graphs (KGs) aims to map entities and relationships into a continuous low-dimensional vector space.
Linmei Hu +6 more
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IEEE Access, 2022 In recent years, although the application of knowledge graph in natural language processing has made some progress, there are still some key problems to be solved, especially the matching query problem in natural language knowledge graph. Since the basic
Qifeng Zou, Chaoze Lu
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Survey on Visualization Query Technology of Knowledge Graph [PDF]
Jisuanji gongcheng, 2020 Knowledge graph,as the development product of symbolism,is considered to be an important part of artificial intelligence technologies and systems,and widely used in encyclopedia knowledge,biological information,social network,network security and so on ...
WANG Xin, FU Qiang, WANG Lin, XU Dawei, WANG Haofen
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Analysis of Knowledge Graph Path Reasoning Based on Variational Reasoning
Applied Sciences, 2022 Knowledge graph (KG) reasoning improves the perception ability of graph structure features, improving model accuracy and enhancing model learning and reasoning capabilities.
Hongmei Tang +5 more
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Frontiers in Big Data, 2023 The knowledge graph is one of the essential infrastructures of artificial intelligence. It is a challenge for knowledge engineering to construct a high-quality domain knowledge graph for multi-source heterogeneous data.
Chenwei Yan +6 more
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Graph Modeling in Computer Assisted Automotive Development
, 2023 203210We consider graph modeling for a knowledge graph for vehicle development, with a focus on crash safety. An organized schema that incorporates information from various structured and unstructured data sources is provided, which includes relevant ...
Pakiman, Anahita, Garcke, Jochen
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RubenVerborgh/Knowledge-Graph-Conference-2022: v1.0.0
, 2022 Slides for my talk at the Knowledge Graph Conference ...
Ruben Verborgh
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Transactions on Graph Data and Knowledge [PDF]
, 2023 Transactions on Graph Data and Knowledge (TGDK) is a new journal publishing peer-reviewed research on graph-based abstractions for data and knowledge, as well as the techniques, theories, applications and results that arise in this setting.
Kagal, Lalana +3 more
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