Declarative Process Discovery: Linking Process and Textual Views
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Standard
Declarative Process Discovery: Linking Process and Textual Views. / López, Hugo A.; Strømsted, Rasmus; Niyodusenga, Jean-Marie; Marquard, Morten.
Intelligent Information Systems: CAiSE Forum 2021 Melbourne, VIC, Australia, June 28 – July 2, 2021 Proceedings. Springer, 2021. s. 109-117 (Lecture Notes in Business Information Processing, Bind 424).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Declarative Process Discovery: Linking Process and Textual Views
AU - López, Hugo A.
AU - Strømsted, Rasmus
AU - Niyodusenga, Jean-Marie
AU - Marquard, Morten
N1 - Conference code: 33
PY - 2021
Y1 - 2021
N2 - Business Process models are conceptual representations of work practices. However, a process is more than its model: key information about the rationale of the process is hidden in accompanying documents. We present a framework for business process discovery from process descriptions in texts. We use declarative process models as our target modelling technique. The manual discovery of declarative process models from texts is particularly hard as users have difficulties identifying textual fragments denoting business rules. Our framework combines machine-learning and expert system techniques in order to provide an algorithmic solution to discovery. The combination of the two techniques allows 1) the identification of process components in texts, 2) the enrichment of predictions with semantic information, and 3) the generation of consolidated hybrid models that link text fragments and process elements. Our initial evaluation reports state-of-the-art performance in accuracy against user annotated models, and it has been implemented and adopted by our industrial partner.
AB - Business Process models are conceptual representations of work practices. However, a process is more than its model: key information about the rationale of the process is hidden in accompanying documents. We present a framework for business process discovery from process descriptions in texts. We use declarative process models as our target modelling technique. The manual discovery of declarative process models from texts is particularly hard as users have difficulties identifying textual fragments denoting business rules. Our framework combines machine-learning and expert system techniques in order to provide an algorithmic solution to discovery. The combination of the two techniques allows 1) the identification of process components in texts, 2) the enrichment of predictions with semantic information, and 3) the generation of consolidated hybrid models that link text fragments and process elements. Our initial evaluation reports state-of-the-art performance in accuracy against user annotated models, and it has been implemented and adopted by our industrial partner.
KW - Faculty of Science
KW - Declarative Process Models
KW - Natural Language Processing
KW - Process elicitation
KW - Process discovery
KW - DCR Graphs
U2 - 10.1007/978-3-030-79108-7_13
DO - 10.1007/978-3-030-79108-7_13
M3 - Article in proceedings
SN - 978-3-030-79107-0
T3 - Lecture Notes in Business Information Processing
SP - 109
EP - 117
BT - Intelligent Information Systems
PB - Springer
T2 - International Conference on Advanced Information Systems Engineering
Y2 - 28 June 2021 through 2 July 2021
ER -
ID: 273366034