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Dataset . 2023
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Dataset . 2022
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Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Evaluation datasets and results for the paper "Enhancing Business Process Simulation Models with Extraneous Activity Delays"

Authors: David Chapela-Campa; Marlon Dumas;

Evaluation datasets and results for the paper "Enhancing Business Process Simulation Models with Extraneous Activity Delays"

Abstract

Event-logs and Business Process Simulation Models used in the experimentation of the paper "Enhancing Business Process Simulation Models with Extraneous Activity Delays", where the 'inputs' folder contains all the files used as input, and the 'output' folder the results of the evaluation. Inputs: event-logs, BPS models, and simulation parameters used as input in the experimentation. Real-life: real-life event logs, corresponding to two disjoint subsets of traces from an Academic Credentials' process, and the BPIC 2012 and BPIC 2017 event logs (filtered as explained in the paper), and the BPS model (plus simulation parameters) used as input for each dataset in the presented approach. Synthetic: simulated event-logs and corresponding BPS models (plus simulation parameters) for four different processes with 0, 1, 3 and 5 timer events. Outputs: results of the experimentation. Real-life: results corresponding to the evaluation with real-life event logs. Each of the folders is composed by the original and the enhanced BPS models, 10 event logs simulated with each of them, two folders with the best iteration of the two hyperparameter optimization processes, and the values for the injected timers in each case. In addition, a CSV file with the EMD metrics (cycle time and absolute hour event distribution) for each dataset is provided. Synthetic: results corresponding to the simulated event-logs. Before-After: BPS models and discovered timer events for the four synthetic processes, with five timers placed before and after different activity instances. Complete: BPS models and quality measures (precision, recall, and SMAPE of the discovered timers) for the four synthetic processes with zero, one, three, and five timer events. Individual: event logs enhanced with the discovered extraneous delay for each activity instance, for the four synthetic processes with zero, one, three, and five timer events; and SMAPE of the estimations.

{"references": ["van Dongen, Boudewijn (2017): BPI Challenge 2017. 4TU.ResearchData. Dataset. https://doi.org/10.4121/uuid:5f3067df-f10b-45da-b98b-86ae4c7a310b", "van Dongen, Boudewijn (2012): BPI Challenge 2012. 4TU.ResearchData. Dataset. https://doi.org/10.4121/uuid:3926db30-f712-4394-aebc-75976070e91f"]}

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Keywords

Real-life Event Log, Process Mining, Extraneous Delays, Business Process Intelligence Challenge

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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