Privacy and confidentiality in process mining: Threats and research challenges
Privacy and confidentiality are very important prerequisites for applying process mining to
comply with regulations and keep company secrets. This article provides a foundation for …
comply with regulations and keep company secrets. This article provides a foundation for …
[PDF][PDF] Turning Big Data into Value: A Literature Review on Business Value Realization from Process Mining.
In recent years, process mining has emerged as the leading Big Data technology for
business process analysis. By extracting knowledge from event logs readily available in …
business process analysis. By extracting knowledge from event logs readily available in …
Recommendations for enhancing the usability and understandability of process mining in healthcare
Healthcare organizations are confronted with challenges including the contention between
tightening budgets and increased care needs. In the light of these challenges, they are …
tightening budgets and increased care needs. In the light of these challenges, they are …
[HTML][HTML] PM4Py: A process mining library for Python
PM4Py is a Python library providing a comprehensive array of tools for process mining. This
paper presents an in-depth overview of the PM4Py library, including its integration with other …
paper presents an in-depth overview of the PM4Py library, including its integration with other …
A new approach for mining correlated frequent subgraphs
Nowadays graphical datasets are having a vast amount of applications. As a result, graph
mining—mining graph datasets to extract frequent subgraphs—has proven to be crucial in …
mining—mining graph datasets to extract frequent subgraphs—has proven to be crucial in …
OWSP-Miner: Self-adaptive one-off weak-gap strong pattern mining
Gap constraint sequential pattern mining (SPM), as a kind of repetitive SPM, can avoid
mining too many useless patterns. However, this method is difficult for users to set a suitable …
mining too many useless patterns. However, this method is difficult for users to set a suitable …
Encoding resource experience for predictive process monitoring
Events recorded during the execution of a business process can be used to train models to
predict, at run-time, the outcome of each execution of the process (aka case). In this setting …
predict, at run-time, the outcome of each execution of the process (aka case). In this setting …
Process-data quality: the true frontier of process mining
Since its emergence over two decades ago, process mining has flourished as a discipline,
with numerous contributions to its theory, widespread practical applications, and mature …
with numerous contributions to its theory, widespread practical applications, and mature …
OrdinoR: A framework for discovering, evaluating, and analyzing organizational models using event logs
In order to streamline business processes and increase competitiveness, organizations
need to have a deep insight into the resources that they deploy. Among others, they need to …
need to have a deep insight into the resources that they deploy. Among others, they need to …
Using big data to improve safety performance: an application of process mining to enhance data visualisation
The management of health and safety plays an important role in safety performance, and is
therefore an important foundational element in an organisation's overall sustainable …
therefore an important foundational element in an organisation's overall sustainable …