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001     1002195
005     20251006154627.0
024 7 _ |2 arXiv
|a arXiv:2401.14149
024 7 _ |2 doi
|a 10.48550/arXiv.2401.14149
024 7 _ |2 datacite_doi
|a 10.18154/RWTH-2025-00398
037 _ _ |a RWTH-2025-00398
041 _ _ |a English
100 1 _ |0 P:(DE-82)IDM05745
|a Küsters, Aaron Ruben
|b 0
|e Corresponding author
|u rwth
245 _ _ |a Developing a High-Performance Process Mining Library with Java and Python Bindings in Rust
|h online
260 _ _ |c 2024
300 _ _ |a 22 Seiten
336 7 _ |0 28
|2 EndNote
|a Electronic Article
336 7 _ |0 PUB:(DE-HGF)25
|2 PUB:(DE-HGF)
|a Preprint
|b preprint
|m preprint
336 7 _ |2 BibTeX
|a ARTICLE
336 7 _ |2 DRIVER
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336 7 _ |2 DataCite
|a Output Types/Working Paper
336 7 _ |2 ORCID
|a WORKING_PAPER
588 _ _ |a Dataset connected to DataCite
591 _ _ |a Germany
650 _ 7 |2 Other
|a FOS: Computer and information sciences
650 _ 7 |2 Other
|a Software Engineering (cs.SE)
653 _ 7 |a FFI
653 _ 7 |a Java
653 _ 7 |a Process Mining
653 _ 7 |a Python
653 _ 7 |a Rust
653 _ 7 |a XES
700 1 _ |0 P:(DE-82)IDM02412
|a van der Aalst, Wil M. P.
|b 1
|e Corresponding author
|u rwth
856 4 _ |u https://publications.rwth-aachen.de/record/1002195/files/1002195.pdf
|y OpenAccess
909 C O |o oai:publications.rwth-aachen.de:1002195
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910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)IDM05745
|a RWTH Aachen
|b 0
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910 1 _ |0 I:(DE-588b)36225-6
|6 P:(DE-82)IDM02412
|a RWTH Aachen
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914 1 _ |y 2024
915 _ _ |0 StatID:(DE-HGF)0510
|2 StatID
|a OpenAccess
915 _ _ |0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
|a Creative Commons Attribution CC BY 4.0
920 1 _ |0 I:(DE-82)122510_20140620
|k 122510
|l Lehrstuhl für Process and Data Science (Informatik 9)
|x 0
920 1 _ |0 I:(DE-82)120000_20140620
|k 120000
|l Fachgruppe Informatik
|x 1
980 1 _ |a FullTexts
980 _ _ |a I:(DE-82)120000_20140620
980 _ _ |a I:(DE-82)122510_20140620
980 _ _ |a UNRESTRICTED
980 _ _ |a VDB
980 _ _ |a preprint

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