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Hierarchical structure and the prediction of missing links in networks

Author

Listed:
  • Aaron Clauset

    (and
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA)

  • Cristopher Moore

    (and
    University of New Mexico, Albuquerque, New Mexico 87131, USA
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA)

  • M. E. J. Newman

    (Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA
    University of Michigan, Ann Arbor, Michigan 48109, USA)

Abstract

Refining the network Networks are now a ubiquitous tool for representing the structure of complex systems, including the Internet, social networks, food webs, and protein and genetic networks. Unfortunately, the data describing these networks are in many cases incomplete or biased. A new study provides a general technique to divide network vertices into groups and sub-groups. Revealing such underlying hierarchies makes it possible to predict missing links from partial data with higher accuracy than previous methods.

Suggested Citation

  • Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    • Handle: RePEc:nat:nature:v:453:y:2008:i:7191:d:10.1038_nature06830
    DOI: 10.1038/nature06830
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