• DOI:10.1109/DSAA.2015.7344816
Corpus ID: 14939580

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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