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View all- Zheng YQu JYang J(2024)StructSim: Meta-Structure-Based Similarity Measure in Heterogeneous Information NetworksApplied Sciences10.3390/app1402093514:2(935)Online publication date: 22-Jan-2024
In this paper, we propose a novel framework to automatically utilize task-dependent semantic information which is encoded in heterogeneous information networks (HINs). Specifically, we search for a meta graph, which can capture more complex semantic ...
Recently, increasing attention has been paid to heterogeneous graph representation learning (HGRL), which aims to embed rich structural and semantic information in heterogeneous information networks (HINs) into low-dimensional node ...
In recent years, heterogeneous graphs, a complex graph structure that can express multiple types of nodes and edges, have been widely used for modeling various real-world scenarios. As a powerful analysis tool, heterogeneous graph neural networks (...
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