Declarative Process Mining

Declarative Process Mining is a process mining approach that discovers and models business processes by extracting high-level, flexible constraints from event data, in contrast to procedural methods that represent processes as rigid sequences of activities.

33

Publications

1.3K

Citations

76

Authors

33

Institutions

Publications per year

2017–2026

18

Authors

76

  1. FM
    Fabrizio Maria Maggi

    University of Tartu, Estonia

    14 publications · 696 citations

    13

    h-index

  2. CD
    Claudio Di Ciccio

    Vienna University of Economics and Business, Austria

    7 publications · 292 citations

    7

    h-index

  3. AS
    Alessandro Sperduti

    University of Padua, Italy

    3 publications · 141 citations

    3

    h-index

  4. JM
    Jan Mendling

    Vienna University of Economics and Business, Austria

    3 publications · 108 citations

    3

    h-index

  5. MM
    Massimo Mecella

    Sapienza University of Rome, Italy

    3 publications · 191 citations

    3

    h-index

1–5 of 76

Venues

  1. Information Systems

    5 publications · 145 citations

    5

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 22 citations

    1

    h-index

  3. BMC Medical Informatics and Decision Making

    1 publications · 14 citations

    1

    h-index

  4. Data Archiving and Networked Services (DANS)

    Repository · 1 publications · 31 citations

    1

    h-index

  5. IEEE Internet Computing

    1 publications · 21 citations

    1

    h-index

1–5