Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants

Summary: Introduces frequent infix-pattern mining over concurrency-aware process variants, where executions are partially ordered rather than sequential. The key reduction to frequent subtree mining enables efficient discovery and outperforms a state-of-the-art method on real event logs. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 13299
Venue: VLDB
Year: 2023
Pagerank: 5.093636e-05
Overall Rank: 11,446 | 21.48%
DOI: 10.14778/3603581.3603603

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Authors

1. Michael Martini (RWTH Aachen University)
2. Daniel Schuster (Fraunhofer Institute; RWTH Aachen University)
3. Wil M.P. van der Aalst (Fraunhofer Institute; RWTH Aachen University)

BibTeX Citation

@article{martini_vldb23,
        title = {{Mining Frequent Infix Patterns from Concurrency-Aware Process Execution Variants}},
        author = {Martini, Michael and Schuster, Daniel and van der Aalst, Wil M.P.},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {10},
        pages = {2666--2678},
        doi = {10.14778/3603581.3603603},
        url = {https://doi.org/10.14778/3603581.3603603},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
27	Fast Algorithms for Mining Association Rules	1994	VLDB	0.00052255472

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