CMV-ND builds one feature view per exact hop distance and then runs existing clustering methods on those views, improving attribute-missing large-scale graph clustering in experiments.
Explicit view-labels matter: A multifacet complementarity study of multi-view clustering
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Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
CMV-ND builds one feature view per exact hop distance and then runs existing clustering methods on those views, improving attribute-missing large-scale graph clustering in experiments.