A comprehensive survey of graph neural networks for knowledge graphs
The Knowledge graph, a multi-relational graph that represents rich factual information
among entities of diverse classifications, has gradually become one of the critical tools for …
among entities of diverse classifications, has gradually become one of the critical tools for …
Representation learning for knowledge fusion and reasoning in Cyber–Physical–Social Systems: Survey and perspectives
The digital deep integration of cyber space, physical space and social space facilitates the
formation of Cyber–Physical–Social Systems (CPSS). Knowledge empowers CPSS to be …
formation of Cyber–Physical–Social Systems (CPSS). Knowledge empowers CPSS to be …
Otkge: Multi-modal knowledge graph embeddings via optimal transport
Multi-modal knowledge graph embeddings (KGE) have caught more and more attention in
learning representations of entities and relations for link prediction tasks. Different from …
learning representations of entities and relations for link prediction tasks. Different from …
Gtp-4o: Modality-prompted heterogeneous graph learning for omni-modal biomedical representation
Recent advances in learning multi-modal representation have witnessed the success in
biomedical domains. While established techniques enable handling multi-modal …
biomedical domains. While established techniques enable handling multi-modal …
Relation-enhanced negative sampling for multimodal knowledge graph completion
Knowledge Graph Completion (KGC), aiming to infer the missing part of Knowledge Graphs
(KGs), has long been treated as a crucial task to support downstream applications of KGs …
(KGs), has long been treated as a crucial task to support downstream applications of KGs …
Hyper-node relational graph attention network for multi-modal knowledge graph completion
Knowledge graphs often suffer from incompleteness, and knowledge graph completion
(KGC) aims at inferring the missing triplets through knowledge graph embedding from …
(KGC) aims at inferring the missing triplets through knowledge graph embedding from …
[HTML][HTML] Achieving cognitive mass personalization via the self-X cognitive manufacturing network: an industrial knowledge graph-and graph embedding-enabled …
Facilitated by cutting-edge information and communication technologies (ICTs), smart
manufacturing is emerging as an overwhelming wave, reforming global manufacturing …
manufacturing is emerging as an overwhelming wave, reforming global manufacturing …
MMKRL: A robust embedding approach for multi-modal knowledge graph representation learning
X Lu, L Wang, Z Jiang, S He, S Liu - Applied Intelligence, 2022 - Springer
Most knowledge representation learning (KRL) methods only use structured knowledge
graphs (KGs); however, there is still much multi-modal (textual, visual) knowledge that has …
graphs (KGs); however, there is still much multi-modal (textual, visual) knowledge that has …
Multimodal Biological Knowledge Graph Completion via Triple Co-attention Mechanism
Biological Knowledge Graphs (BKGs) can help to model complex biological systems in a
structural way to support various tasks. Nevertheless, the incompleteness problem may limit …
structural way to support various tasks. Nevertheless, the incompleteness problem may limit …
Knowledge graph embedding based on graph neural network
S Liang - 2023 IEEE 39th International Conference on Data …, 2023 - ieeexplore.ieee.org
The representation of semantic information pertaining to the real world has been active
research for some time now. Among the available methods, knowledge graphs have …
research for some time now. Among the available methods, knowledge graphs have …