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The subnetwork investigation of scale-free networks based on the self-similarity

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  • Wang, Wenting
  • Shi, Shijie
  • Fu, Xianghua

Abstract

The scale-free network with self-similarity is an essential data structure widely used in social networks and bioinformatics. The subnetwork investigation of large-scale networks has attracted attention in many applications. Traditional methods are computationally complexity and time-consuming. A new methodology needs to handle the computational complexity challenge from large-scale network datasets. In this paper, we develop a series of edge-based subnetwork investigation algorithms: HEPS-1 and HEPS-2. We investigate the relations between edges and their edge neighbours caused by the reconcile of scale-free and self-similarity. Then, we determine the edges for the subnetwork. In this way, we sample the networks while keeping the original statistical characters. The computational complexity is low. The effectiveness of sampling is enhanced.

Suggested Citation

  • Wang, Wenting & Shi, Shijie & Fu, Xianghua, 2022. "The subnetwork investigation of scale-free networks based on the self-similarity," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    • Handle: RePEc:eee:chsofr:v:161:y:2022:i:c:s0960077922003502
    DOI: 10.1016/j.chaos.2022.112140
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    References listed on IDEAS

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    1. Jarod Y. L. Lee & James J. Brown & Louise M. Ryan, 2017. "Sufficiency Revisited: Rethinking Statistical Algorithms in the Big Data Era," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 202-208, July.
    2. Qi Gao & Xintong Ding & Feng Pan & Weixing Li, 2014. "An improved sampling method of complex network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(05), pages 1-11.
    3. Chaoming Song & Shlomo Havlin & Hernán A. Makse, 2005. "Self-similarity of complex networks," Nature, Nature, vol. 433(7024), pages 392-395, January.
    4. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    5. Faraway, Julian J. & Augustin, Nicole H., 2018. "When small data beats big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 142-145.
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