Predicting Case Suffixes With Activity Start and End Times: A Sweep-Line Based Approach

• URL: http://arxiv.org/abs/2509.14536v1
• Date: Thu, 18 Sep 2025 02:01:30 GMT
• Title: Predicting Case Suffixes With Activity Start and End Times: A Sweep-Line Based Approach
• Authors: Muhammad Awais Ali, Marlon Dumas, Fredrik Milani,
• Abstract summary: This paper introduces a technique for predicting case suffixes consisting of activities with start and end timestamps.<n>The proposed technique predicts both the waiting time and the processing time of each activity.<n>An evaluation on real-life and synthetic datasets compares the accuracy of different instantiations of this approach.
• Score: 0.35684665108045377
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Predictive process monitoring techniques support the operational decision making by predicting future states of ongoing cases of a business process. A subset of these techniques predict the remaining sequence of activities of an ongoing case (case suffix prediction). Existing approaches for case suffix prediction generate sequences of activities with a single timestamp (e.g. the end timestamp). This output is insufficient for resource capacity planning, where we need to reason about the periods of time when resources will be busy performing work. This paper introduces a technique for predicting case suffixes consisting of activities with start and end timestamps. In other words, the proposed technique predicts both the waiting time and the processing time of each activity. Since the waiting time of an activity in a case depends on how busy resources are in other cases, the technique adopts a sweep-line approach, wherein the suffixes of all ongoing cases in the process are predicted in lockstep, rather than predictions being made for each case in isolation. An evaluation on real-life and synthetic datasets compares the accuracy of different instantiations of this approach, demonstrating the advantages of a multi-model approach to case suffix prediction.

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