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2024 | OriginalPaper | Buchkapitel

Computing Motifs in Hypergraphs

verfasst von : Duarte Nóbrega, Pedro Ribeiro

Erschienen in: Complex Networks XV

Verlag: Springer Nature Switzerland

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Abstract

Motifs are overrepresented and statistically significant sub-patterns in a network, whose identification is relevant to uncover its underlying functional units. Recently, its extraction has been performed on higher-order networks, but due to the complexity arising from polyadic interactions, and the similarity with known computationally hard problems, its practical application is limited. Our main contribution is a novel approach for hyper-subgraph census and higher-order motif discovery, allowing for motifs with sizes 3 or 4 to be found efficiently, in real-world scenarios. It is consistently an order of magnitude faster than a baseline state-of-art method, while using less memory and supporting a wider range of base algorithms.

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Fußnoten
1
All the hypergraph images were created using [8].
 
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Metadaten
Titel
Computing Motifs in Hypergraphs
verfasst von
Duarte Nóbrega
Pedro Ribeiro
Copyright-Jahr
2024
DOI
https://doi.org/10.1007/978-3-031-57515-0_5

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