HOEG: A New Approach for Object-Centric Predictive Process Monitoring
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61057-8_14
Reference15 articles.
1. van der Aalst, W.M.P., Berti, A.: Discovering object-centric petri nets. Fundam. Inform. 175(1–4), 1–40 (2020)
2. Adams, J.N., Park, G., Levich, S., Schuster, D., van der Aalst, W.M.P.: A framework for extracting and encoding features from object-centric event data. In: Troya, J., Medjahed, B., Piattini, M., Yao, L., Fernandez, P., Ruiz-Cortes, A. (eds.) Service-Oriented Computing. ICSOC 2022. LNCS, vol. 13740, pp. 36–53. Springer, Cham (2022). https://doi.org/10.1007/978-3-031-20984-0_3
3. Adams, J.N., Schuster, D., Schmitz, S., Schuh, G., van der Aalst, W.M.P.: Defining cases and variants for object-centric event data. In: ICPM, pp. 128–135. IEEE (2022)
4. Berti, A., Herforth, J., Qafari, M.S., van der Aalst, W.M.P.: Graph-based feature extraction on object-centric event logs. Int. J. Data Sci. Anal. (2023)
5. van Dongen, B.F.: Bpi challenge 2017 (2017)
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