The HIM glocal metric and kernel for network comparison and classification

@article{Jurman2015TheHG,
  title={The HIM glocal metric and kernel for network comparison and classification},
  author={Giuseppe Jurman and R. Visintainer and M. Filosi and S. Riccadonna and C. Furlanello},
  journal={2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)},
  year={2015},
  pages={1-10}
}
  • Giuseppe Jurman, R. Visintainer, +2 authors C. Furlanello
  • Published 2015
  • Mathematics, Computer Science, Physics
  • 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA)
  • Comparing and classifying graphs represent two essential steps for network analysis, across different scientific and applicative domains. Here we deal with both operations by introducing the Hamming-Ipsen-Mikhailov (HIM) distance, a novel metric to quantitatively measure the difference between two graphs sharing the same vertices. The new measure combines the local Hamming edit distance and the global Ipsen-Mikhailov spectral distance so to overcome the drawbacks affecting the two components… CONTINUE READING
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