A spectral algorithm with additive clustering for the recovery of overlapping communities in networks

DOI10.1016/j.tcs.2017.12.028zbMath1398.68442arXiv1506.04158OpenAlexW3023166002MaRDI QIDQ1663638

Emilie Kaufmann, Thomas Bonald, Marc Lelarge

Publication date: 22 August 2018

Published in: Theoretical Computer Science, Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1506.04158

zbMATH Keywords

community detectionstochastic blockmodel

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Social networks; opinion dynamics (91D30) Random graphs (graph-theoretic aspects) (05C80) Learning and adaptive systems in artificial intelligence (68T05) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50)

Related Items (3)

Estimating Mixed Memberships With Sharp Eigenvector Deviations ⋮ Community Detection and Stochastic Block Models ⋮ Detecting Overlapping Communities in Networks Using Spectral Methods

Uses Software

• SNAP
• k-means++

Cites Work

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• Overlapping stochastic block models with application to the French political blogosphere
• Spectral clustering and the high-dimensional stochastic blockmodel
• User-friendly tail bounds for sums of random matrices
• Consistency of community detection in networks under degree-corrected stochastic block models
• Matrix estimation by universal singular value thresholding
• Consistency of spectral clustering in stochastic block models
• Spectral redemption in clustering sparse networks
• Mixed membership stochastic blockmodels
• Overlapping community detection in networks
• Elements of Information Theory
• The Rotation of Eigenvectors by a Perturbation. III

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