Discovering Responsibilities with Dynamic Condition Response Graphs
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Discovering Responsibilities with Dynamic Condition Response Graphs. / Nekrasaite, Viktorija; Parli, Andrew Tristan; Back, Christoffer Olling; Slaats, Tijs.
Advanced Information Systems Engineering: 31st International Conference, CAiSE 2019, Rome, Italy, June 3–7, 2019, Proceedings. red. / Paolo Giorgini; Barbara Weber. 31. udg. Springer, 2019. s. 595-610 (Lecture Notes in Computer Science, Bind 11483).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Discovering Responsibilities with Dynamic Condition Response Graphs
AU - Nekrasaite, Viktorija
AU - Parli, Andrew Tristan
AU - Back, Christoffer Olling
AU - Slaats, Tijs
PY - 2019/6/3
Y1 - 2019/6/3
N2 - 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.
AB - 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.
KW - Faculty of Science
KW - Declarative process discovery
KW - Declarative models
KW - Dynamic Condition Response Graphs
KW - DCR Graphs
KW - DCR Discovery
U2 - 10.1007/978-3-030-21290-2_37
DO - 10.1007/978-3-030-21290-2_37
M3 - Article in proceedings
SN - 978-3-030-21289-6
T3 - Lecture Notes in Computer Science
SP - 595
EP - 610
BT - Advanced Information Systems Engineering
A2 - Giorgini, Paolo
A2 - Weber, Barbara
PB - Springer
T2 - 31th International Conference on Advanced Information Systems Engineering (CAiSE 2019)
Y2 - 3 June 2019 through 7 June 2019
ER -
ID: 222547291