Clique counts for network similarity
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866911750232735744 |
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| author | Bonato, Anthony Zhang, Zhiyuan |
| author_facet | Bonato, Anthony Zhang, Zhiyuan |
| contents | Counts of small subgraphs, or graphlet counts, are widely applicable to measure graph similarity. Computing graphlet counts can be computationally expensive and may pose obstacles in network analysis. We study the role of cliques in graphlet counts as a method for graph similarity in social networks. Higher-order clustering coefficients and the Pivoter algorithm for exact clique counts are employed |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_03536 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Clique counts for network similarity Bonato, Anthony Zhang, Zhiyuan Social and Information Networks Counts of small subgraphs, or graphlet counts, are widely applicable to measure graph similarity. Computing graphlet counts can be computationally expensive and may pose obstacles in network analysis. We study the role of cliques in graphlet counts as a method for graph similarity in social networks. Higher-order clustering coefficients and the Pivoter algorithm for exact clique counts are employed |
| title | Clique counts for network similarity |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2401.03536 |