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Extending predictive process monitoring for collaborative processes

arXiv 2409.09212 ↗First posted 13 Sep 2024cs.DB cs.LGcited by 0

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Abstract (arXiv)

Process mining on business process execution data has focused primarily on orchestration-type processes performed in a single organization (intra-organizational). Collaborative (inter-organizational) processes, unlike those of orchestration type, expand several organizations (for example, in e-Government), adding complexity and various challenges both for their implementation and for their discovery, prediction, and analysis of their execution. Predictive process monitoring is based on exploiting execution data from past instances to predict the execution of current cases. It is possible to make predictions on the next activity and remaining time, among others, to anticipate possible deviations, violations, and delays in the processes to take preventive measures (e.g., re-allocation of resources). In this work, we propose an extension for collaborative processes of traditional process prediction, considering particularities of this type of process, which add information of interest in this context, for example, the next activity of which participant or the following message to be exchanged between two participants.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 66 references that are in the map. First posted on arXiv 13 Sep 2024.

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References · 12

  1. 2017Attention Is All You Needcited by 60,361
  2. 2016Predictive Business Process Monitoring with LSTM Neural Networkscited by 104
  3. 2020Deep Learning for Predictive Business Process Monitoring: Review and Benchmarkcited by 45
  4. 2013Predictive Monitoring of Business Processescited by 37
  5. 2017Outcome-Oriented Predictive Process Monitoring: Review and Benchmarkcited by 37
  6. 2021ProcessTransformer: Predictive Business Process Monitoring with Transformer Networkcited by 37
  7. 2016Time and Activity Sequence Prediction of Business Process Instancescited by 24
  8. 2017LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instancescited by 19
  9. 2022Object-centric Process Predictive Analyticscited by 6
  10. 2019Secure Multi-Party Computation for Inter-Organizational Process Miningcited by 4
  11. 2024HOEG: A New Approach for Object-Centric Predictive Process Monitoringcited by 2
  12. 2022Nirdizati: an Advanced Predictive Process Monitoring Toolkitcited by 1

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