SOTAVerified

Community Detection

Community Detection is one of the fundamental problems in network analysis, where the goal is to find groups of nodes that are, in some sense, more similar to each other than to the other nodes.

Source: Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–325 of 919 papers

TitleStatusHype
Machine-Learning Based Objective Function Selection for Community DetectionCode0
Spectral Algorithms Optimally Recover Planted Sub-structures—0
Perturbation Analysis of Randomized SVD and its Applications to Statistics—0
Graph Neural Networks for Multiparallel Word Alignment—0
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—0
Sparse random hypergraphs: Non-backtracking spectra and community detectionCode0
High-order Order Proximity-Incorporated, Symmetry and Graph-Regularized Nonnegative Matrix Factorization for Community Detection—0
Fast Community Detection based on Graph Autoencoder Reconstruction—0
Bayesian community detection for networks with covariatesCode0
Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks—0
Near-Optimal Correlation Clustering with Privacy—0
Listing Maximal k-Plexes in Large Real-World GraphsCode0
Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle—0
Geometric Graph Representation Learning via Maximizing Rate Reduction—0
A Semi-Supervised Deep Clustering Pipeline for Mining Intentions From Texts—0
An Adaptive Deep Clustering Pipeline to Inform Text Labeling at Scale—0
Machine learning to assess relatedness: the advantage of using firm-level data—0
Differentially Private Community Detection for Stochastic Block Models—0
Why the Rich Get Richer? On the Balancedness of Random Partition Models—0
The effect of the pandemic on complex socio-economic systems: community detection induced by communicability—0
Detecting Communities in Complex Networks using an Adaptive Genetic Algorithm and node similarity-based encoding—0
Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community LabelingCode0
Multiway Spherical Clustering via Degree-Corrected Tensor Block Models—0
Graph-Based Recommendation System Enhanced with Community Detection—0
Investigating internal migration with network analysis and latent space representations: An application to Turkey—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GNNAccuracy-NE2—Unverified
2CommunityGANF1-score0.09—Unverified
3Ego-SplittingF1-score0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1EdMotNMI0.42—Unverified
2CDNMFNMI0.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1CommunityGANF1-Score0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.69—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.68—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.67—Unverified