Deep cut-informed graph embedding and clustering

doi:10.1016/j.inffus.2025.103603

Deep cut-informed graph embedding and clustering

2025-08-10

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DOI：10.1016/j.inffus.2025.103603

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Abstract

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• Investigate graph clustering from a graph cut perspective. • Proposing a novel and non-GNN-based graph clustering paradigm, DCGC. • A cut-informed graph encoding module to fuse graph structure and node attributes. • Self-supervised graph clustering via optimal transport.

Keywords:

graph clustering

graph cut

non-GNN-based

cut-informed encoding

optimal transport

Deep cut-informed graph embedding and clustering

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