Hypergraph clustering using Ricci curvature: an edge transport perspective
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866911237977145344 |
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| author | Hacquard, Olympio |
| author_facet | Hacquard, Olympio |
| contents | In this paper, we introduce a novel method for extending Ricci flow to hypergraphs by defining probability measures on the edges and transporting them on the line expansion. This approach yields a new weighting on the edges, which proves particularly effective for community detection. We extensively compare this method with a similar notion of Ricci flow defined on the clique expansion, demonstrating its enhanced sensitivity to the hypergraph structure, especially in the presence of large hyperedges. The two methods are complementary and together form a powerful and highly interpretable framework for community detection in hypergraphs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_15695 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Hypergraph clustering using Ricci curvature: an edge transport perspective Hacquard, Olympio Machine Learning Social and Information Networks In this paper, we introduce a novel method for extending Ricci flow to hypergraphs by defining probability measures on the edges and transporting them on the line expansion. This approach yields a new weighting on the edges, which proves particularly effective for community detection. We extensively compare this method with a similar notion of Ricci flow defined on the clique expansion, demonstrating its enhanced sensitivity to the hypergraph structure, especially in the presence of large hyperedges. The two methods are complementary and together form a powerful and highly interpretable framework for community detection in hypergraphs. |
| title | Hypergraph clustering using Ricci curvature: an edge transport perspective |
| topic | Machine Learning Social and Information Networks |
| url | https://arxiv.org/abs/2412.15695 |