Results 11 to 20 of about 35,565 (288)
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
doaj +4 more sources
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
doaj +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
doaj +3 more sources
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
doaj +3 more sources
Temporal Knowledge Graph Completion: A Survey
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023 Knowledge graph completion (KGC) predicts missing links and is crucial for real-life knowledge graphs, which widely suffer from incompleteness. KGC methods assume a knowledge graph is static, but that may lead to inaccurate prediction results because many facts in the knowledge graphs change over time.
Borui Cai +5 more
core +5 more sources
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
doaj +3 more sources
Semantic-Enhanced Knowledge Graph Completion
MathematicsKnowledge graphs (KGs) serve as structured representations of knowledge, comprising entities and relations. KGs are inherently incomplete, sparse, and have a strong need for completion.
Xu Yuan +6 more
doaj +3 more sources
Generative Transformer with Knowledge-Guided Decoding for Academic Knowledge Graph Completion
Mathematics, 2023 Academic knowledge graphs are essential resources and can be beneficial in widespread real-world applications. Most of the existing academic knowledge graphs are far from completion; thus, knowledge graph completion—the task of extending a knowledge ...
Xiangwen Liu +3 more
doaj +2 more sources
Progressive Knowledge Graph Completion
CoRRKnowledge Graph Completion (KGC) has emerged as a promising solution to address the issue of incompleteness within Knowledge Graphs (KGs). Traditional KGC research primarily centers on triple classification and link prediction. Nevertheless, we contend that these tasks do not align well with real-world scenarios and merely serve as surrogate benchmarks.
Jiayi Li 0002 +4 more
openaire +3 more sources
Few-Shot Knowledge Graph Completion
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Knowledge graphs (KGs) serve as useful resources for various natural language processing applications. Previous KG completion approaches require a large number of training instances (i.e., head-tail entity pairs) for every relation. The real case is that for most of the relations, very few entity pairs are available.
Chuxu Zhang +5 more
openaire +4 more sources