ISSN 0253-2778

CN 34-1054/N

Open AccessOpen Access JUSTC Research Article

Link prediction in complex networks based on mutual information

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2020.01.007
  • Received Date: 31 March 2018
  • Rev Recd Date: 21 December 2018
  • Publish Date: 31 January 2020
  • A new perspective of dealing with link prediction problem was derived due to the application of mutual information in complex networks. Traditional mutual information algorithm (MI) not only considers the neighbor information of nodes, but also the structural information of common neighbors. Although MI has better performance compared with traditional methods which are based on common neighbors, it doesn’t effectively differentiate between different common neighbors. A new algorithm (MMI) was proposed by considering the influence of different common neighbors, which performs better than MI in precision.
    A new perspective of dealing with link prediction problem was derived due to the application of mutual information in complex networks. Traditional mutual information algorithm (MI) not only considers the neighbor information of nodes, but also the structural information of common neighbors. Although MI has better performance compared with traditional methods which are based on common neighbors, it doesn’t effectively differentiate between different common neighbors. A new algorithm (MMI) was proposed by considering the influence of different common neighbors, which performs better than MI in precision.
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