Multi-view graph contrastive clustering via consensus constraint

doi:10.1016/j.neucom.2026.133069

Multi-view graph contrastive clustering via consensus constraint

2026-02-16

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DOI：10.1016/j.neucom.2026.133069

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Abstract

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• We propose MGC4 for multi-view graph contrastive clustering. • The method constructs positive pairs via inter-view structural consensus. • An adaptive weighting strategy distinguishes positives of varying importance. • Experiments on six datasets demonstrate superior accuracy and robustness.

Keywords:

Multi-view graph clustering

Graph contrastive learning

Structural consensus

Adaptive weighting

Clustering accuracy

Multi-view graph contrastive clustering via consensus constraint

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