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 451–500 of 919 papers

TitleStatusHype
Spectral Algorithms for Community Detection in Directed Networks—0
Community models for networks observed through edge nominations—0
Big Networks: A Survey—0
A Novel Community Detection Based Genetic Algorithm for Feature Selection—0
Community detection in sparse latent space models—0
Almost exact recovery in noisy semi-supervised learningCode0
Integrating Network Embedding and Community Outlier Detection via Multiclass Graph DescriptionCode0
Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective—0
IncNSA: Detecting communities incrementally from time-evolving networks based on node similarityCode1
GRADE: Graph Dynamic Embedding—0
Extended Stochastic Block Models with Application to Criminal NetworksCode1
Evaluating Community Detection Algorithms for Progressively Evolving Graphs—0
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?—0
Next Waves in Veridical Network Embedding—0
Community detection and Social Network analysis based on the Italian wars of the 15th century—0
On spectral algorithms for community detection in stochastic blockmodel graphs with vertex covariatesCode0
Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings—0
Towards analyzing large graphs with quantum annealing and quantum gate computers—0
Non-Convex Exact Community Recovery in Stochastic Block ModelCode0
Community detection and percolation of information in a geometric setting—0
Statistical inference of assortative community structuresCode0
Clustering with Tangles: Algorithmic Framework and Theoretical GuaranteesCode1
An _p theory of PCA and spectral clustering—0
Community-Based Data Integration of Course and Job Data in Support of Personalized Career-Education Recommendations—0
Applying Machine Learning Techniques for Caching in Edge Networks: A Comprehensive Survey—0
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clusteringCode0
Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France—0
Interferometric Graph Transform: a Deep Unsupervised Graph RepresentationCode1
Graph Neural Network Encoding for Community Detection in Attribute NetworksCode0
Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling—0
Community detection in sparse time-evolving graphs with a dynamical Bethe-HessianCode0
Revealing consensus and dissensus between network partitionsCode0
p-Norm Flow Diffusion for Local Graph ClusteringCode1
Deep Learning for Community Detection: Progress, Challenges and OpportunitiesCode1
Neural Stochastic Block Model & Scalable Community-Based Graph Learning—0
Sampling Community Structure—0
Knowledge Graph semantic enhancement of input data for improving AI—0
Evolutionary Multi Objective Optimization Algorithm for Community Detection in Complex Social Networks—0
Community Detection Clustering via Gumbel Softmax—0
Finding structural hole spanners based on community forest model and diminishing marginal utility in large scale social networks—0
Assortative-Constrained Stochastic Block ModelsCode0
Strong Consistency, Graph Laplacians, and the Stochastic Block Model—0
Word Embedding-based Text Processing for Comprehensive Summarization and Distinct Information Extraction—0
Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and PerformanceCode1
Recommendation system using a deep learning and graph analysis approachCode0
Provable Overlapping Community Detection in Weighted Graphs—0
Encoder blind combinatorial compressed sensing—0
Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach—0
Reliable Time Prediction in the Markov Stochastic Block ModelCode0
Detecting Communities in Heterogeneous Multi-Relational Networks:A Message Passing based Approach—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