The Social Process Mining Cockpit: A Collaboration Pattern Detection Tool for Enterprise Collaboration Systems
Dirk Fahland; Andrés Jiménez Ramírez; Akhil Kumar; Jan Mendling; Brian Pentland; Stefanie Rinderle-Ma; Tijs Slaats; Johan Versendaal; Barbara Weber; Mathias Weske; Karol Winter (Hrsg). Proceedings of the Best Dissertation Award, Doctoral Consortium, and Demonstration & Resources Forum co-located with 21st International Conference on Business Process Management (BPM 2023): Utrecht, The Netherlands, September 11th to 15th, 2023. Aachen: CEUR/RWTH 2023 S. 132 - 136
Erscheinungsjahr: 2023
ISBN/ISSN: 1613-0073
Publikationstyp: Diverses (Konferenzbeitrag)
Sprache: Englisch
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Inhaltszusammenfassung
Social Process Mining (SPM) combines the research fields Process Mining (PM) and Social Collaboration Analytics. The SPM-Cockpit is a prototype that can detect and analyze Collaboration Patterns in event logs of Enterprise Collaboration Systems (ECS) semi-automatically. We use this tool to investigate activity patterns that occur while users work collaboratively in ECS. To do so, we adapt methods from Process Mining, Frequent Subgraph Mining, and Graph Clustering and bundle them in the SPM-Co...Social Process Mining (SPM) combines the research fields Process Mining (PM) and Social Collaboration Analytics. The SPM-Cockpit is a prototype that can detect and analyze Collaboration Patterns in event logs of Enterprise Collaboration Systems (ECS) semi-automatically. We use this tool to investigate activity patterns that occur while users work collaboratively in ECS. To do so, we adapt methods from Process Mining, Frequent Subgraph Mining, and Graph Clustering and bundle them in the SPM-Cockpit. The prototype is a first step towards investigating, understanding and categorizing collaboration activity in ECS automatically.» weiterlesen» einklappen
