Irene Teinemaa

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Business process enactment is generally supported by information systems that record data about process executions, which can be extracted as event logs. Predictive process monitoring is concerned with exploiting such event logs to predict how running (uncompleted) cases will unfold up to their completion. In this paper, we propose a predictive process(More)
The Decision Model and Notation (DMN) is a standard notation to capture decision logic in business applications in general and business processes in particular. A central construct in DMN is that of a decision table. The increasing use of DMN decision tables to capture critical business knowledge raises the need to support analysis tasks on these tables(More)
A key problem for facilitators of online communication and social networks is to identify users whose activity is likely to change in the near future. Such predictions may serve as basis for targeted campaigns aimed at sustaining or increasing overall user engagement in the network. A common approach to this problem is to apply machine learning methods to(More)
Predictive process monitoring is concerned with exploiting event logs to predict how running (uncompleted) cases will unfold up to their completion. In this paper, we propose an implementation in the ProM toolset of a predictive process monitoring framework for estimating the probability that an ongoing case will lead to a certain outcome among a set of(More)
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