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Resources for Graph Data and Knowledge [PDF]
Transactions on Graph Data and KnowledgeIn this Special Issue of Transactions on Graph Data and Knowledge - entitled "Resources for Graph Data and Knowledge" - we present eight articles that describe key resources in the area.
Hogan, Aidan +4 more
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Entity Profiling in Knowledge Graphs
IEEE Access, 2020 Knowledge Graphs (KGs) are graph-structured knowledge bases storing factual information about real-world entities. Understanding the uniqueness of each entity is crucial to the analyzing, sharing, and reusing of KGs.
Xiang Zhang +3 more
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Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2020 Knowledge Graphs can be considered as fulfilling an early vision in Computer Science of creating intelligent systems that integrate knowledge and data at large scale. Stemming from scientific advancements in research areas of Semantic Web, Databases, Knowledge representation, NLP, Machine Learning, among others, Knowledge Graphs have rapidly gained ...
Claudio Gutierrez, Juan F. Sequeda
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Survey of Research on Knowledge Graph Based on Pre-trained Language Models [PDF]
Jisuanji kexueIn the era of large language models(LLMs),knowledge graphs(KGs),as a structured representation of knowledge,play an irreplaceable role in enhancing the reliability,security,and interpretability of artificial intelligence.With its superior performance in ...
ZENG Zefan, HU Xingchen, CHENG Qing, SI Yuehang, LIU Zhong
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Text-Graph Enhanced Knowledge Graph Representation Learning [PDF]
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. Conventional KG embedding methods (such as TransE and ConvE) utilize only KG triplets and thus suffer from structure
Linmei Hu +6 more
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Applications of knowledge graphs for food science and industry
Patterns, 2022 Summary: The deployment of various networks (e.g., Internet of Things [IoT] and mobile networks), databases (e.g., nutrition tables and food compositional databases), and social media (e.g., Instagram and Twitter) generates huge amounts of food data ...
Weiqing Min +3 more
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Survey of Research on Curriculum Knowledge Graph Construction Techniques [PDF]
Jisuanji gongchengIn the context of ongoing advancements in educational informatization, constructing precise and efficient curriculum knowledge graphs has become key to promoting personalized education development.
SUN Lijun, MENG Fanjun, XU Xingjian
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Noisy Knowledge Graph Representation Learning: a Rule-Enhanced Method [PDF]
Jisuanji kexue yu tansuo, 2023 Knowledge graphs are used to store structured facts, which are presented in the form of triples, i.e., (head entity, relation, tail entity). Current large-scale knowledge graphs are usually constructed with (semi-) automated methods for knowledge ...
SHAO Tianyang, XIAO Weidong, ZHAO Xiang
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BioMedInformatics, 2023 Semantic web technologies (SWT) represent data in a format that is easier for machines to understand. Validating the knowledge in data graphs created using SWT is critical to ensure that the axioms accurately represent the so-called “real” world. However,
Rashmi Burse +2 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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