Supporting Confidentiality in Process Mining Using Abstraction and Encryption-Reference-Cited by-同舟云学术

Supporting Confidentiality in Process Mining Using Abstraction and Encryption

Published:2020 Issue: Volume: Page:101-123
ISSN:1865-1348
Container-title:Lecture Notes in Business Information Processing
language:
Short-container-title:

Author:

Rafiei Majid^ORCID,von Waldthausen Leopold^ORCID,van der Aalst Wil M. P.^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-46633-6_6

Reference31 articles.

1. van der Aalst, W.M.P.: Business process management: a comprehensive survey. ISRN Softw. Eng. 2013, 1–37 (2013)

2. van der Aalst, W.M.P.: Process Mining - Data Science in Action, Second edn. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-49851-4

3. Lecture Notes in Business Information Processing;WMP van der Aalst,2017

4. van der Aalst, W.M.P.: Benchmarking logs to test scalability of process discovery algorithms. Eindhoven University of Technology (2017). https://data.4tu.nl/repository/uuid:1cc41f8a-3557-499a-8b34-880c1251bd6e . Accessed 01 Apr 2018

5. van der Aalst, W.M.P.: Process discovery from event data: relating models and logs through abstractions. Wiley Interdiscip. Rev.: Data Mining Knowl. Discov. 8(3), e1244 (2018)

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