In this paper, we take a step towards a principled method of network composition from multi-layer data. We argue that inter-layer dynamics is a essential component of understanding the structure as a whole. Mathematically, we consider the following abstract problem: given multiple layers of network data over a shared vertex set, and additional parameters for inter-layer transitions, construct a (single) weighted network that best integrates the multi-layer dynamics. In this context, we will also study an empirical use case of the composition framework.
CITATION STYLE
Yan, X., Teng, S. H., & Lerman, K. (2017). Multi-layer network composition under a unified dynamical process. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10354 LNCS, pp. 315–321). Springer Verlag. https://doi.org/10.1007/978-3-319-60240-0_38
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