Comparative Analysis of Structural Backbone Extraction Techniques
Résumé
This study explores structural backbone extraction methods in diverse real-world
networks, ranging from character to social networks. Eight techniques from the netbone pack-
age are analyzed using Jaccard and Overlap coefficients to measure similarities. The Kolmogorov–Smirnov statistic evaluates weight and degree distribution preservation. Results highlight correlations and hierarchical relationships among techniques, with Doubly Stochastic outperforming in mimicking original network distributions. The study’s comprehensive insights contribute to refining and advancing structural filtering techniques, fostering a deeper understanding of complex systems.
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