Declarative Process Mining for DCR Graphs
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Declarative Process Mining for DCR Graphs. / Debois, Søren; Hildebrandt, Thomas T.; Laursen, Paw Høvsgaard; Ulrik, Kenneth Ry.
Proceedings of the Symposium on Applied Computing: SAC '17. New York, NY, USA : Association for Computing Machinery, 2017. p. 759-764.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Declarative Process Mining for DCR Graphs
AU - Debois, Søren
AU - Hildebrandt, Thomas T.
AU - Laursen, Paw Høvsgaard
AU - Ulrik, Kenneth Ry
N1 - Conference code: 32
PY - 2017
Y1 - 2017
N2 - We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.
AB - We investigate process mining for the declarative Dynamic Condition Response (DCR) graphs process modelling language. We contribute (a) a process mining algorithm for DCR graphs, (b) a proposal for a set of metrics quantifying output model quality, and (c) a preliminary example-based comparison with the Declare Maps Miner. The algorithm takes a contradiction-based approach, that is, we initially assume that all possible constraints hold, subsequently removing constraints as they are observed to be violated by traces in the input log.
U2 - 10.1145/3019612.3019622
DO - 10.1145/3019612.3019622
M3 - Article in proceedings
SN - 978-1-4503-4486-9
SP - 759
EP - 764
BT - Proceedings of the Symposium on Applied Computing
PB - Association for Computing Machinery
CY - New York, NY, USA
T2 - The 32nd ACM SIGAPP Symposium On Applied Computing
Y2 - 4 April 2017
ER -
ID: 227990236