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

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Showing 576–600 of 919 papers

TitleStatusHype
Higher-order Knowledge Transfer for Dynamic Community Detection with Great Changes—0
Higher-Order Spectral Clustering under Superimposed Stochastic Block Model—0
High-order Order Proximity-Incorporated, Symmetry and Graph-Regularized Nonnegative Matrix Factorization for Community Detection—0
High Quality, Scalable and Parallel Community Detectionfor Large Real Graphs—0
How is a data-driven approach better than random choice in label space division for multi-label classification?—0
How Many Communities Are There?—0
How Robust are Reconstruction Thresholds for Community Detection?—0
Human-Centric Community Detection in Hybrid Metaverse Networks with Integrated AI Entities—0
Hyperbolic Multiplex Network Embedding with Maps of Random Walk—0
Hypergraph clustering using Ricci curvature: an edge transport perspective—0
Hypothesis Testing for Automated Community Detection in Networks—0
Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion—0
Identifying Linked Fraudulent Activities Using GraphConvolution Network—0
IEDC: An Integrated Approach for Overlapping and Non-overlapping Community Detection—0
Implicit models, latent compression, intrinsic biases, and cheap lunches in community detection—0
Improved Deep Embeddings for Inferencing with Multi-Layered Networks—0
Improved mutual information measure for classification and community detection—0
Improving Community Detection Performance in Heterogeneous Music Network by Learning Edge-type Usefulness Distribution—0
Improving Fine-Tuning with Latent Cluster Correction—0
Improving Smart Conference Participation through Socially-Aware Recommendation—0
Improving Twitter Community Detection through Contextual Sentiment Analysis—0
Incremental Community Detection in Distributed Dynamic Graph—0
Incremental Eigenpair Computation for Graph Laplacian Matrices: Theory and Applications—0
Incremental Method for Spectral Clustering of Increasing Orders—0
Induced Modularity and Community Detection for Functionally Interpretable Reinforcement Learning—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