MGCN-FLC improves multi-view GCN node classification by using granular-ball topology construction, inter-feature enhancement, and interactive cross-view fusion to exploit three forms of consistency.
Sdhgcn: A heterogeneous graph convolutional neural net- work combined with shadowed set.IEEE Transactions on Fuzzy Systems
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Multi-view Graph Convolutional Network with Fully Leveraging Consistency via Granular-ball-based Topology Construction, Feature Enhancement and Interactive Fusion
MGCN-FLC improves multi-view GCN node classification by using granular-ball topology construction, inter-feature enhancement, and interactive cross-view fusion to exploit three forms of consistency.