CM++ - A Meta-method for Well-Connected Community Detection

Python R Submitted 29 October 2023 • Published 19 January 2024
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Editor: @arfon (all papers)
Reviewers: @LuisScoccola (all reviews), @chryswoods (all reviews)

Authors

Vikram Ramavarapu (0009-0001-8875-7213), Fábio Jose Ayres (0009-0000-6821-4687), Minhyuk Park (0000-0002-8676-7565), Vidya Kamath Pailodi (0009-0000-0987-5901), João Alfredo Cardoso Lamy (0009-0005-4744-4754), Tandy Warnow (0000-0001-7717-3514), George Chacko (0000-0002-2127-1892)

Citation

Ramavarapu et al., (2024). CM++ - A Meta-method for Well-Connected Community Detection. Journal of Open Source Software, 9(93), 6073, https://doi.org/10.21105/joss.06073

@article{Ramavarapu2024, doi = {10.21105/joss.06073}, url = {https://doi.org/10.21105/joss.06073}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {93}, pages = {6073}, author = {Vikram Ramavarapu and Fábio Jose Ayres and Minhyuk Park and Vidya Kamath Pailodi and João Alfredo Cardoso Lamy and Tandy Warnow and George Chacko}, title = {CM++ - A Meta-method for Well-Connected Community Detection}, journal = {Journal of Open Source Software} }
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CM++ connectivity minimum cut complex network analysis graph network degree clustering

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066