Community detection in the sparse hypergraph stochastic block model

Soumik Pal; Yizhe Zhu

doi:10.1002/rsa.21006

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arXiv · 1904.05981

Community detection in the sparse hypergraph stochastic block model

Soumik Pal·Yizhe Zhu

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Abstract

We consider the community detection problem in sparse random hypergraphs. Angelini et al. (2015) conjectured the existence of a sharp threshold on model parameters for community detection in sparse hypergraphs generated by a hypergraph stochastic block model. We solve the positive part of the conjecture for the case of two blocks: above the threshold, there is a spectral algorithm which asymptotically almost surely constructs a partition of the hypergraph correlated with the true partition. Our method is a generalization to random hypergraphs of the method developed by Massouli\'{e} (2014) for sparse random graphs.

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BibTeX RIS

Soumik Pal, Yizhe Zhu. 2019-04-11. Community detection in the sparse hypergraph stochastic block model. https://doi.org/10.1002/rsa.21006

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