Generating multi-level explanations for process outcome predictions-Reference-Cited by-同舟云学术

Generating multi-level explanations for process outcome predictions

Published:2023-10 Issue: Volume:125 Page:106678
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Wickramanayake Bemali,Ouyang Chun,Xu Yue,Moreira Catarina

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference57 articles.

1. TensorFlow: Large-scale machine learning on heterogeneous systems;Abadi,2015

2. COGAM: Measuring and moderating cognitive load in machine learning model explanations;Abdul,2020

3. Towards robust interpretability with self-explaining neural networks;Alvarez-Melis,2018

4. Process mining-driven optimization of a consumer loan approvals process;Bautista,2013

5. Learning accurate LSTM models of business processes;Camargo,2019

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Validation set sampling strategies for predictive process monitoring;Information Systems;2024-03

2. Uncovering the Hidden Significance of Activities Location in Predictive Process Monitoring;Lecture Notes in Business Information Processing;2024

3. Uncovering Patterns for Local Explanations in Outcome-Based Predictive Process Monitoring;Lecture Notes in Computer Science;2024

4. Towards Scalable Process Mining Pipelines;2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech);2023-11-14