Tuning Machine Learning to Address Process Mining Requirements-Reference-Cited by-同舟云学术

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Tuning Machine Learning to Address Process Mining Requirements

Published:2024 Issue: Volume:12 Page:24583-24595
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ceravolo Paolo¹^ORCID,Junior Sylvio Barbon²^ORCID,Damiani Ernesto³^ORCID,Van Der Aalst Wil⁴^ORCID

Affiliation:

1. Department of Computer Science, University of Milan, Milan, Italy

2. Department of Engineering and Architecture, University of Trieste, Trieste, Italy

3. Department of Electrical Engineering and Computer Science, Khalifa University, Abu Dhabi, United Arab Emirates

4. Chair of Process and Data Science, RWTH Aachen University, Aachen, Germany

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10418930.pdf?arnumber=10418930

Reference97 articles.

1. Process Mining Manifesto

2. Advancing Process Audits With Process Mining: A Systematic Review of Trends, Challenges, and Opportunities

3. Process mining: software comparison, trends, and challenges

4. Welcome to the Era of ChatGPT et al.

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1. Human Activity Recognition with Unsupervised Learning of Event Logs;Journal of Computer Information Systems;2024-09-06

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