Investigating Social Contextual Factors in Remaining-Time Predictive Process Monitoring—A Survival Analysis Approach
Predictive process monitoring aims to accurately predict a variable of interest (e.g., remaining time) or the future state of the process instance (e.g., outcome or next step). The quest for models with higher predictive power has led to the development of a variety of novel approaches. However, tho...
Main Authors: | Niyi Ogunbiyi, Artie Basukoski, Thierry Chaussalet |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/13/11/267 |
Similar Items
-
Investigating the Diffusion of Workload-Induced Stress—A Simulation Approach
by: Niyi Ogunbiyi, et al.
Published: (2020-12-01) -
Parallel-Structure Deep Learning for Prediction of Remaining Time of Process Instances
by: Nur Ahmad Wahid, et al.
Published: (2021-10-01) -
An Exploration of Ethical Decision Making with Intelligence Augmentation
by: Niyi Ogunbiyi, et al.
Published: (2021-02-01) -
Context-Aware Process Performance Indicator Prediction
by: Alfonso E. Marquez-Chamorro, et al.
Published: (2020-01-01) -
An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements
by: Baoli Wei, et al.
Published: (2022-09-01)