{"ID":2896608,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.10570","arxiv_id":"2507.10570","title":"Local Clustering in Hypergraphs through Higher-Order Motifs","abstract":"Hypergraphs provide a powerful framework for modeling complex systems and networks with higher-order interactions beyond simple pairwise relationships. However, graph-based clustering approaches, which focus primarily on pairwise relations, fail to represent higher-order interactions, often resulting in low-quality clustering outcomes. In this work, we introduce a novel approach for local clustering in hypergraphs based on higher-order motifs, small connected subgraphs in which nodes may be linked by interactions of any order, extending motif-based techniques previously applied to standard graphs. Our method exploits hypergraph-specific higher-order motifs to better characterize local structures and optimize motif conductance. We propose two alternative strategies for identifying local clusters around a seed hyperedge: a core-based method utilizing hypergraph core decomposition and a BFS-based method based on breadth-first exploration. We construct an auxiliary hypergraph to facilitate efficient partitioning and introduce a framework for local motif-based clustering. Extensive experiments on real-world datasets demonstrate the effectiveness of our framework and provide a comparative analysis of the two proposed clustering strategies in terms of clustering quality and computational efficiency.","short_abstract":"Hypergraphs provide a powerful framework for modeling complex systems and networks with higher-order interactions beyond simple pairwise relationships. However, graph-based clustering approaches, which focus primarily on pairwise relations, fail to represent higher-order interactions, often resulting in low-quality clu...","url_abs":"https://arxiv.org/abs/2507.10570","url_pdf":"https://arxiv.org/pdf/2507.10570v1","authors":"[\"Giuseppe F. Italiano\",\"Athanasios L. Konstantinidis\",\"Anna Mpanti\",\"Fariba Ranjbar\"]","published":"2025-07-09T14:28:08Z","proceeding":"cs.SI","tasks":"[\"cs.SI\"]","methods":"[\"LoRA\"]","has_code":false}