Explainable concept drift in process mining-Reference-Cited by-同舟云学术

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Explainable concept drift in process mining

Published:2023-03 Issue: Volume:114 Page:102177
ISSN:0306-4379
Container-title:Information Systems
language:en
Short-container-title:Information Systems

Author:

Adams Jan Niklas^ORCID,van Zelst Sebastiaan J.,Rose Thomas,van der Aalst Wil M.P.

Funder

Alexander von Humboldt-Stiftung

Publisher

Elsevier BV

Subject

Hardware and Architecture,Information Systems,Software

Reference63 articles.

1. Fundamentals of Business Process Management;Dumas,2018

2. Process Mining: Data Science in Action;van der Aalst,2016

3. Discovering block-structured process models from event logs - A constructive approach;Leemans,2013

4. Conformance checking using cost-based fitness analysis;Adriansyah,2011

5. Automated discovery of business process simulation models from event logs;Camargo;Decis. Support Syst.,2020

Cited by 20 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. Detecting and rationalizing concept drift: A feature-level approach for understanding cause-effect relationships in dynamic environments;Expert Systems with Applications;2024-09

2. Detecting Process Duration Drift Using Gamma Mixture Models in a Left-Truncated and Right-Censored Environment;ACM Transactions on Knowledge Discovery from Data;2024-08-21

3. Dynamic Classification Ensembles for Handling Imbalanced Multiclass Drifted Data Streams;Information Sciences;2024-06

4. Thwarting Cybersecurity Attacks with Explainable Concept Drift;2024 International Wireless Communications and Mobile Computing (IWCMC);2024-05-27

5. FBDD: feature-based drift detector for batch processing data;Cluster Computing;2024-03-08

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