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} }
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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References
SHOWING 1-10 OF 138 REFERENCES
Learning an Integrated Distance Metric for Comparing Structure of Complex Networks
- Computer Science, Physics
- ArXiv
- 2013
- 3
- PDF
Empirical comparison of graph classification algorithms
- Computer Science
- 2009 IEEE Symposium on Computational Intelligence and Data Mining
- 2009
- 26
- PDF
Distance metric learning for complex networks: towards size-independent comparison of network structures.
- Mathematics, Medicine
- Chaos
- 2015
- 21
- PDF
Bridging the Gap between Graph Edit Distance and Kernel Machines
- Mathematics, Computer Science
- Series in Machine Perception and Artificial Intelligence
- 2007
- 190
- PDF