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Chemical reaction network knowledge graphs: the OntoRXN ontology [PDF]
, 2022 : The organization and management of large amounts of data has become a major point in almost all areas of human knowledge. In this context, semantic approaches propose a structure for the target data, defining ontologies that state the types of entities
Bo, Carles +3 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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Narrativizing Knowledge Graphs
, 2022 Any natural language expression of a set of facts – that can be represented as a knowledge graph – will more or less overtly assume a specific perspective on these facts. In this paper we see the conversion of a given knowledge graph into natural language as the construction of a narrative about the assertions made by the knowledge graph. We, therefore,
Porzel, Robert +5 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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Embedding-Based First-Order Rule Learning in Large Knowledge Graphs
, 2023 Numerous large knowledge graphs, such as DBpedia, Wikidata, Yago and Freebase, have been developed in the last decade, which contain millions of facts about various entities in the world.
Omran, PG, Wang, Z, Wang, K, Wu, H
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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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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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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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Knowledge formalization in experience feedback processes : an ontology-based approach [PDF]
, 2008 Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous
Kamsu-Foguem, Bernard +3 more
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