2022
DOI: 10.1007/978-3-031-21534-6_2
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Generating Synthetic Graph Data from Random Network Models

Abstract: Network models are developed and used in various fields of science as their design and analysis can improve the understanding of the numerous complex systems we can observe on an everyday basis. From an algorithmics point of view, structural insights into networks can guide the engineering of tailor-made graph algorithms required to face the big data challenge.By design, network models describe graph classes and therefore can often provide meaningful synthetic instances whose applications include experimental … Show more

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