Generative hypergraph clustering: From blockmodels to modularity-Reference-Cited by-同舟云学术

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Generative hypergraph clustering: From blockmodels to modularity

Published:2021-07-09 Issue:28 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Chodrow Philip S.¹^ORCID,Veldt Nate²^ORCID,Benson Austin R.³

Affiliation:

1. Department of Mathematics, University of California, Los Angeles, 520 Portola Plaza, Los Angeles, CA 90095, USA.

2. Center for Applied Mathematics, Cornell University, 657 Frank H.T. Rhodes Hall, Ithaca, NY 14853, USA.

3. Department of Computer Science, Cornell University, 413B Gates Hall, Ithaca, NY 14853, USA.

Abstract

Novel clustering techniques enable the detection of modules in large datasets with multiway interactions.

Funder

National Science Foundation

Army Research Office

JPMorgan Chase and Company

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference77 articles.

1. M. O. Jackson Social and Economic Networks (Princeton Univ. Press 2008).

2. D. Easley J. Kleinberg Networks Crowds and Markets: Reasoning about a Highly Connected World (Cambridge Univ. Press 2010).

3. M. E. J. Newman Networks: An Introduction (Oxford Univ. Press 2010).

4. Network Motifs: Simple Building Blocks of Complex Networks

5. Higher-order organization of complex networks

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