Samenvatting
Classical process mining aims to capture the behavior of a process based on a single dimension: the sequence of activities grouped by process cases. This viewpoint fails to capture how individual actors are organizing their work across multiple cases. We present a tool that uses the graph database Neo4j to model actor behavior over different cases as an event graph. We then use Neo4j queries to detect task execution patterns in the graph describing how multiple actors collaborate across multiple cases. Exploring and visualizing these patterns enables the data driven analysis of tasks, routines, and habits as studied in organizations research.
| Originele taal-2 | Engels |
|---|---|
| Titel | ICPM 2021 Doctoral Consortium and Demo Track 2021 |
| Subtitel | Proceedings of the ICPM Doctoral Consortium and Demo Track 2021 co-located with 10th International Conference on Process Mining (ICPM 2021) |
| Redacteuren | Mieke Jans, Gert Janssenswillen, Anna Kalenkova , Fabrizio Maria Maggi |
| Uitgeverij | CEUR-WS.org |
| Pagina's | 49-50 |
| Aantal pagina's | 2 |
| Status | Gepubliceerd - 2021 |
| Evenement | 3rd International Conference on Process Mining, ICPM 2021 - Eindhoven, Nederland Duur: 31 okt. 2021 → 4 nov. 2021 Congresnummer: 3 |
Publicatie series
| Naam | CEUR Workshop Proceedings |
|---|---|
| Uitgeverij | CEUR-WS.org |
| Volume | 3098 |
| ISSN van geprinte versie | 1613-0073 |
Congres
| Congres | 3rd International Conference on Process Mining, ICPM 2021 |
|---|---|
| Verkorte titel | ICPM 2021 |
| Land/Regio | Nederland |
| Stad | Eindhoven |
| Periode | 31/10/21 → 4/11/21 |
Bibliografische nota
Publisher Copyright:Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).