Applied Network Science, Journal Year: 2024, Volume and Issue: 9(1)

Published: July 22, 2024

Abstract As networks grow in size and complexity, backbones become an essential network representation. Indeed, they provide a simplified yet informative overview of the underlying organization by retaining most significant structurally influential connections within network. Network heterogeneity often results complex intricate structures, making it challenging to identify backbone. In response, we introduce Multilevel Backbone Extraction Framework, novel approach that diverges from conventional backbone methodologies. This generic prioritizes mesoscopic networks. First, splits into homogeneous-density components. Second, extracts independent for each component using any classical technique. Finally, various are combined. strategy effectively addresses observed groupings. Empirical investigations on real-world underscore efficacy preserving structures properties. Experiments demonstrate its superiority over methods handling enhancing integrity. The framework is adaptable types extraction techniques, versatile tool analysis across diverse applications.

Language: Английский