Abstract
Declarative process discovery is the art of using historical data to better understand the responsibilities of an organisation: its governing business rules and goals. These rules and goals can be described using declarative process notations, such as Dynamic Condition Response (DCR) Graphs, which has seen widespread industrial adoption within Denmark, in particular through its integration in a case management solution used by 70% of central government institutions. In this paper, we introduce ParNek: a novel, effective, and extensible miner for the discovery of DCR Graphs. We empirically evaluate ParNek and show that it significantly outperforms the state-of-the-art in DCR discovery and performs at least comparably to the state-of-the-art in Declare discovery. Notably, the miner can be configured to sacrifice relatively little precision in favour of significant gains in simplicity, making it the first miner able to produce understandable DCR Graphs for real-life logs.
This work is supported by the Hybrid Business Process Management Technologies project (DFF-6111-00337) funded by the Danish Council for Independent Research, and the EcoKnow project (7050-00034A) funded by the Innovation Foundation. First and second author listed alphabetically.
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Nekrasaite, V., Parli, A.T., Back, C.O., Slaats, T. (2019). Discovering Responsibilities with Dynamic Condition Response Graphs. In: Giorgini, P., Weber, B. (eds) Advanced Information Systems Engineering. CAiSE 2019. Lecture Notes in Computer Science(), vol 11483. Springer, Cham. https://doi.org/10.1007/978-3-030-21290-2_37
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