DCBM community detection is reformulated as constrained nonnegative matrix factorization, producing a scalable method with strong initialization that matches inference quality on large graphs.
The resulting networks have community sizes between 20 and 100, leading to 16 to 24 commu- nities per network
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Matrix Factorization Framework for Community Detection under the Degree-Corrected Block Model
DCBM community detection is reformulated as constrained nonnegative matrix factorization, producing a scalable method with strong initialization that matches inference quality on large graphs.