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Found 10 papers, 0 papers with code
Bipartite mixed membership distribution-free model. A novel model for community detection in overlapping bipartite weighted networks
To close this gap, we introduce a novel model, the Bipartite Mixed Membership Distribution-Free (BiMMDF) model.
Mixed membership distribution-free model
We also propose the fuzzy weighted modularity to evaluate the quality of community detection for overlapping weighted networks with positive and negative edge weights.
Community detection for weighted bipartite networks
Here, to model a weighted bipartite network, we introduce a Bipartite Distribution-Free model by releasing ScBM's distribution restriction.
Directed mixed membership stochastic blockmodel
DiMMSB allows that row nodes and column nodes of the adjacency matrix can be different and these nodes may have distinct community structure in a directed network.
Estimating Mixed-Memberships Using the Symmetric Laplacian Inverse Matrix
Mixed membership community detection is a challenging problem.
Mixed-SCORE+ for mixed membership community detection
In the note Jin et al. (2018), the authors propose SCORE+ as an improvement of SCORE to handle with weak signal networks.
Consistency of regularized spectral clustering in degree-corrected mixed membership model
Here, under the degree-corrected mixed membership (DCMM) model, we propose an efficient approach called mixed regularized spectral clustering (Mixed-RSC for short) based on the regularized Laplacian matrix.
An improved spectral clustering method for community detection under the degree-corrected stochastic blockmodel
For community detection problem, spectral clustering is a widely used method for detecting clusters in networks.
Dual regularized Laplacian spectral clustering methods on community detection
Spectral clustering methods are widely used for detecting clusters in networks for community detection, while a small change on the graph Laplacian matrix could bring a dramatic improvement.
Community Detection by Principal Components Clustering Methods
Based on the classical Degree Corrected Stochastic Blockmodel (DCSBM) model for network community detection problem, we propose two novel approaches: principal component clustering (PCC) and normalized principal component clustering (NPCC).
