破布
发表于 2025-3-30 08:37:51
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venous-leak
发表于 2025-3-30 15:51:46
Biotechnology in Agriculture and Forestrythose interfaces. Both refinement and sub-processes are then constructed in terms of that composition. Sub-processes take the form of hierarchical (complex) events, which dynamically instantiate sub-processes. The extensions are realised and supported by a prototype simulation tool.
Confidential
发表于 2025-3-30 18:28:12
https://doi.org/10.1007/978-3-662-08618-6n strategies to face the following problems: to find the best discovery algorithm for the data at hand, and to allow bridging the gap between general users and process mining algorithms. Experiments performed with the developed tool witness the usefulness of the approach for a variety of instances.
AVOID
发表于 2025-3-30 20:44:15
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保守党
发表于 2025-3-31 02:37:36
P. Gastaldo,A. M. Caviglia,P. Profumoational applications. This concept relies on BPM standards, Aspect Oriented Programming, and Web patterns to transparently weave business models among current web applications. A prototype platform is presented, which includes our design of a distributed architecture, and a natural and expressive DSL.
意外的成功
发表于 2025-3-31 05:49:40
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MELON
发表于 2025-3-31 12:59:11
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灾祸
发表于 2025-3-31 15:33:50
Medicinal and Aromatic Plants IXhing the next two models, and so forth. This approach improves the matching quality, as showcased by a comparative evaluation. From this study, we also derive strategies on how to maximize the quality while limiting the additional effort required from the user.
Cupping
发表于 2025-3-31 21:01:38
T. Ichi,T. Shimizu,K. Yoshihiramodel discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process discovery techniques.
有节制
发表于 2025-4-1 01:01:57
P. Gastaldo,A. M. Caviglia,P. Profumoher for the most suitable solution from top to bottom using ”soft” constraints and behaviour approximations. The key parts of the algorithm are formally described and evaluation results are presented and discussed.