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A type-augmented knowledge graph embedding framework for knowledge graph completion [PDF]
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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Knowledge Graph Completion: A Review [PDF]
IEEE Access, 2020 Knowledge graph completion (KGC) is a hot topic in knowledge graph construction and related applications, which aims to complete the structure of knowledge graph by predicting the missing entities or relationships in knowledge graph and mining unknown ...
Zhe Chen +5 more
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A Review of Knowledge Graph Completion
Information, 2022 Information extraction methods proved to be effective at triple extraction from structured or unstructured data. The organization of such triples in the form of (head entity, relation, tail entity) is called the construction of Knowledge Graphs (KGs ...
Mohamad Zamini +2 more
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Tuck-KGC: based on tensor decomposition for diabetes knowledge graph completion model integrating Chinese and Western medicine [PDF]
PeerJ Computer ScienceThe medical knowledge graph is essential for intelligent medical services, encompassing personalized diagnostics, precision therapies, and intelligent consultations, among others.
Jiangtao ZhangSun +4 more
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Drug repurposing for COVID-19 via knowledge graph completion [PDF]
Journal of Biomedical Informatics, 2021 Dimitar Hristovski +2 more
exaly +2 more sources
Knowledge Graph Completion With Pattern-Based Methods
IEEE AccessKnowledge graphs (KGs) are popularly used to develop several intelligent applications. Revealing valuable knowledge hidden in these graphs opened up a branch of research, known as KG reasoning, aiming at predicting the missing links.
Maryam Sabet +2 more
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Adaptive Attention-based Knowledge Graph Completion [PDF]
Jisuanji kexue, 2022 Existing knowledge graph completion models learn a single static feature representation for entities and relationships by integrating multi-source information.But they can't represent the subtle meaning and dynamic attributes of entities and ...
WANG Jie, LI Xiao-nan, LI Guan-yu
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Survey on Inductive Learning for Knowledge Graph Completion [PDF]
Jisuanji kexue yu tansuo, 2023 Knowledge graph completion can make knowledge graph more complete. However, traditional knowledge graph completion methods assume that all test entities and relations appear in the training process.
LIANG Xinyu, SI Guannan, LI Jianxin, TIAN Pengxin, AN Zhaoliang, ZHOU Fengyu
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Knowledge Graph Completeness: A Systematic Literature Review [PDF]
IEEE Access, 2021 The quality of a Knowledge Graph (also known as Linked Data) is an important aspect to indicate its fitness for use in an application. Several quality dimensions are identified, such as accuracy, completeness, timeliness, provenance, and accessibility, which are used to assess the quality. While many prior studies offer a landscape view of data quality
Issa, Subhi +5 more
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QubitE:Qubit Embedding for Knowledge Graph Completion [PDF]
Jisuanji kexue, 2023 The knowledge graph completion task completes the knowledge graph by predicting missing facts in the knowledge graph.The quantum-based knowledge graph embedding(KGE) model uses variational quantum circuits to score triples by mea-suring the probability ...
LIN Xueyuan, E Haihong , SONG Wenyu, LUO Haoran, SONG Meina
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