A common problem in process mining is the interpretation of the time stamp of events, e.g., whether it represents the moment of recording, or its occurrence. Often, this interpretation is left implicit. In this paper, we make this interpretation explicit using time intervals: an event occurs somewhere during a time window. The time window may be fine, e.g., a single point in time, or coarse, like a day. As each event is related to an activity within some process, we obtain for each activity a set of intervals in which the activity occurred. Based on these sets of intervals, we define ordering and simultaneousness relations. These relations form the basis of the discovery of a declarative process model describing the behavior in the event log.
|Title of host publication||International Workshop on Modeling and Business Environments (ModBE'13, Milano, Italy, June 24, 2013)|
|Publication status||Published - 2013|
|Name||CEUR Workshop Proceedings|