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Among the many sources of event data available today, a prominent one is userinteraction data. User activity may be recorded during the use of anapplication or website, resulting in a type of user interaction data oftencalled click data. An obstacle to the analysis of click data using processmining is the lack of a case identifier in the data. In this paper, we show acase and user study for event-case correlation on click data, in the context ofuser interaction events from a mobility sharing company. To reconstruct thecase notion of the process, we apply a novel method to aggregate userinteraction data in separate user sessions-interpreted as cases-based on neuralnetworks. To validate our findings, we qualitatively discuss the impact ofprocess mining analyses on the resulting well-formed event log throughinterviews with process experts.

Uncertain Case Identifiers in Process Mining: A User Study of the Event-Case Correlation Problem on Click Data