Comparing temporal graphs using dynamic time warping
@article{Froese2020ComparingTG, title={Comparing temporal graphs using dynamic time warping}, author={Vincent Froese and Brijnesh J. Jain and R. Niedermeier and M. Renken}, journal={Social Network Analysis and Mining}, year={2020}, volume={10}, pages={1-16} }
Within many real-world networks, the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different temporal graphs. To this end, we propose to study dynamic time warping on temporal graphs. We define the dynamic temporal graph warping (dtgw) distance to determine the dissimilarity of two temporal graphs. Our novel measure is flexible and can be applied in… CONTINUE READING
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