The design of temporal networks typically follows a top-down approach where a designer handcrafts a temporal network to model some concrete plan of interest. Instead, the bottom-up approach of mining is the process of building a temporal network from a set of execution traces of some (typically unknown) underlying process. Recent research showed that, due to the structural properties of temporal networks, such a task can be done in polynomial time. In this paper, we give an overview of the current status of our research and highlight open problems concerning Formal Methods and Artificial Intelligence.
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