Unveiling the role of higher-order interactions via stepwise reduction
Abstract Complex systems usually feature interactions not only between pairwise entities but also among three or more entities. Hypergraph can effectively characterize these higher-order interactions. Meanwhile, all higher-order interactions can also be projected onto a number of lower-order interac...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02157-3 |
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| Summary: | Abstract Complex systems usually feature interactions not only between pairwise entities but also among three or more entities. Hypergraph can effectively characterize these higher-order interactions. Meanwhile, all higher-order interactions can also be projected onto a number of lower-order interactions. Determining whether all higher-order interactions must be considered or if they can be approximated by lower-order interactions with minimal loss remains an open question. We propose a method to decompose higher-order structures in a stepwise way, thereby allowing to explore the impacts of hyperedges of any order. Experiments suggest that in some networks, incorporating higher-order interactions significantly enhances the accuracy of link prediction, while in others, the effect is insignificant. Therefore, the role of higher-order interactions varies in different types of networks. Overall, since the improvement in predictive accuracy provided by higher-order interactions is significant in some networks, we believe that the study of higher-order interactions is valuable. |
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| ISSN: | 2399-3650 |