Heterogeneous Graph Attention Network
Beijing University of Posts and Telecommunications · West Virginia University · +2 more institutions
Abstract
Graph neural network, as a powerful graph representation technique based on deep learning, has shown superior performance and attracted considerable research interest. However, it has not been fully considered in graph neural network for heterogeneous graph which contains different types of nodes and links. The heterogeneity and rich semantic information bring great challenges for designing a graph neural network for heterogeneous graph. Recently, one of the most exciting advancements in deep learning is the attention mechanism, whose great potential has been well demonstrated in various areas. In this paper, we first propose a novel heterogeneous graph neural network based on the hierarchical attention,…
Citation impact
- FWCI
- 159.74
- Percentile
- 100%
- References
- 45
Authors
7Topics & keywords
- Computer science
- Interpretability
- Attention network
- Graph
- Theoretical computer science
- Power graph analysis
- Artificial intelligence
- Artificial neural network