Machine-Learning Based Objective Function Selection for Community Detection
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-07689-3_10
Reference39 articles.
1. Ahn, Y.Y., Bagrow, J.P., Lehmann, S.: Link communities reveal multiscale complexity in networks. Nature 466(7307), 761–764 (2010). https://doi.org/10.1038/nature09182
2. Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech. Theory Exp. 2008(10), P10008 (2008). https://doi.org/10.1088/1742-5468/2008/10/p10008
3. Bornstein, A., Rubin, A., Hendler, D.: Machine-learning based objective function selection for community detection (2022). https://doi.org/10.48550/ARXIV.2203.13495. https://arxiv.org/abs/2203.13495
4. Lecture Notes in Computer Science;U Brandes,2007
5. Chen, M., Kuzmin, K., Szymanski, B.K.: Extension of modularity density for overlapping community structure. In: 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014), pp. 856–863 (2014). https://doi.org/10.1109/ASONAM.2014.6921686
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