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pro vyhledávání: '"Brunk, Jens"'
Predictive business process monitoring (PBPM) is a class of techniques designed to predict behaviour, such as next activities, in running traces. PBPM techniques aim to improve process performance by providing predictions to process analysts, support
Externí odkaz:
http://arxiv.org/abs/2008.07993
Predicting undesirable events during the execution of a business process instance provides the process participants with an opportunity to intervene and keep the process aligned with its goals. Few approaches for tackling this challenge consider a mu
Externí odkaz:
http://arxiv.org/abs/2007.07549
Publikováno v:
In Information Systems January 2021 95
Autor:
Stierle, Matthias, Brunk, Jens, Weinzierl, Sven, Zilker, Sandra, Matzner, Martin, Becker, Jörg
Predictive business process monitoring (PBPM) provides a set of techniques to perform different prediction tasks in running business processes, such as the next activity, the process outcome, or the remaining time. Nowadays, deep-learning-based techn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2091::d33ac471d1cee7d6fa411823de6ec0b3
https://opus4.kobv.de/opus4-fau/files/16886/ECIS2021_xpbpm.pdf
https://opus4.kobv.de/opus4-fau/files/16886/ECIS2021_xpbpm.pdf
Autor:
Weinzierl, Sven, Zilker, Sandra, Brunk, Jens, Revoredo, Kate, Nguyen, An, Matzner, Martin, Becker, Jörg, Eskofier, Björn
Researchers have proposed a variety of predictive business process monitoring (PBPM) techniques aiming to predict future process behaviour during the process execution. Especially, techniques for the next activity prediction anticipate great potentia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d5300015b3542ac87582c028d160438
Autor:
Brunk, Jens1 (AUTHOR) jens.brunk@ercis.uni-muenster.de, Stottmeister, Johannes1 (AUTHOR), Weinzierl, Sven2 (AUTHOR), Matzner, Martin2 (AUTHOR), Becker, Jörg1 (AUTHOR)
Publikováno v:
Journal of Decision Systems. 2020 Supplement, Vol. 29, p328-343. 16p.
Publikováno v:
Proceedings of the European Conference on Information Systems (ECIS); 2018, p1-16, 16p