Predictive business process monitoring aims at forecasting the future information of a running business process based on the models extracted from business process execution logs (event logs). This tool, which is called SDPROM v2, is a prototype that implements the Specification-Driven Predictive Business Process Monitoring approach introduced in [1, 2]. This prototype extends the previous version in https://github.com/ariosantoso/Specification-Driven-Predictive-Process-Monitoring/tree/V1, and the extension is based on our recent journal paper that has been published in [1].
It is a ProM plug-in, and it enables us to
- specify the desired prediction tasks using the language that is introduced in [1, 2], and
- create the corresponding prediction models based on the given specification.
Once the prediction models has been created, they can be used to provide predictive analysis service in business process monitoring. The screencast of this tool, which explains the way how to use our tool (ProM plug-in), can be found in http://bit.ly/sdprom2-screencast. The user manual of our tools (including the instructions on how to reproduce our experiments) can be found in http://bit.ly/sdprom2-manual. The binary distribution (.jar) of this tool can be found in http://bit.ly/sdprom2-dist. More information about this work can be found in http://bit.ly/sdprom2.
The following picture illustrates our approach:
This project is licensed under the GNU General Public License v3.0
Specification-Driven-Predictive-Process-Monitoring
Copyright (C) 2018 Ario Santoso (santoso.ario@gmail.com)
Licensed under GNU General Public License v3.0.
You may obtain a copy of the License at
http://www.gnu.org/licenses/
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
This project is a Maven project. Thus, compiling and building the release binaries can be done using maven in the usual way. Currently we use Maven 3 and Java 8 to build the project.
For more information or if you find any problem regarding this work, please contact the author:
Ario Santoso
Email: santoso[dot]ario[at]gmail[dot]com
Homepage: http://bit.ly/ariosantoso
If you use our work (e.g., our software) please cite this work. You may use the following bibtex entries in order to cite this work:
@Article{SF-SOSYM-19,
author="Ario Santoso and Michael Felderer",
title="Specification-driven predictive business process monitoring",
journal="International Journal on Software and Systems Modeling (SoSym)",
year="2019",
doi="https://doi.org/10.1007/s10270-019-00761-w"
}
@incollection{AS-BPMDS-18,
author = “Ario Santoso”,
title = "Specification-Driven Multi-Perspective Predictive Business Process Monitoring",
booktitle = "Enterprise, Business-Process and Information Systems Modeling, BPMDS 2018, EMMSAD 2018",
series = "Lecture Notes in Business Information Processing",
volume="318",
pages="97-113",
publisher = "Springer",
year = "2018”,
doi="https://doi.org/10.1007/978-3-319-91704-7_7"
}
[1] Ario Santoso, Michael Felderer (2019): Specification-Driven Predictive Business Process Monitoring. In International Journal on Software and Systems Modeling (SoSym). DOI: https://doi.org/10.1007/s10270-019-00761-w.
[2] Ario Santoso (2018): Specification-Driven Multi-Perspective Predictive Business Process Monitoring. In Enterprise, Business-Process and Information Systems Modeling, BPMDS 2018, EMMSAD 2018. LNBIP. vol 318. pages 97-113. Springer.
[3] Ario Santoso (2018): Specification-Driven Multi-Perspective Predictive Business Process Monitoring (Extended Version). CoRR Technical Report arXiv:1804.00617, arXiv.org e-Print archive, available at https://arxiv.org/abs/1804.00617.