Abstract
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.
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Yan, X., Teng, SH., Lerman, K. (2017). Multi-layer Network Composition Under a Unified Dynamical Process. In: Lee, D., Lin, YR., Osgood, N., Thomson, R. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2017. Lecture Notes in Computer Science(), vol 10354. Springer, Cham. https://doi.org/10.1007/978-3-319-60240-0_38
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DOI: https://doi.org/10.1007/978-3-319-60240-0_38
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