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 601–625 of 919 papers

TitleStatusHype
Inference of hidden structures in complex physical systems by multi-scale clustering—0
Inference via Message Passing on Partially Labeled Stochastic Block Models—0
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction—0
Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings—0
Information-theoretic Limits for Community Detection in Network Models—0
Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection—0
Integration of graph clustering with ant colony optimization for feature selection—0
Intelligent Anti-Money Laundering Solution Based upon Novel Community Detection in Massive Transaction Networks on Spark—0
International Trade Network: Country centrality and COVID-19 pandemic—0
Introducing the modularity graph: an application to brain functional networks—0
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?—0
Investigating internal migration with network analysis and latent space representations: An application to Turkey—0
Ising-Based Louvain Method: Clustering Large Graphs with Specialized Hardware—0
Joint community and anomaly tracking in dynamic networks—0
Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science—0
Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science—0
KAN KAN Buff Signed Graph Neural Networks?—0
Kernel k-Groups via Hartigan's Method—0
Knowledge Graph semantic enhancement of input data for improving AI—0
Laplacian Mixture Modeling for Network Analysis and Unsupervised Learning on Graphs—0
Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining—0
Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data—0
Latent Geometry Inspired Graph Dissimilarities Enhance Affinity Propagation Community Detection in Complex Networks—0
Latent heterogeneous multilayer community detection—0
Leaders, Followers, and Community Detection—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