A survey on concept drift in process mining
Concept drift in process mining (PM) is a challenge as classical methods assume processes
are in a steady-state, ie, events share the same process version. We conducted a systematic …
are in a steady-state, ie, events share the same process version. We conducted a systematic …
Business process management: a comprehensive survey
WMP Van der Aalst - International Scholarly Research Notices, 2013 - Wiley Online Library
Business Process Management (BPM) research resulted in a plethora of methods,
techniques, and tools to support the design, enactment, management, and analysis of …
techniques, and tools to support the design, enactment, management, and analysis of …
Process mining for python (PM4Py): bridging the gap between process-and data science
Process mining, ie, a sub-field of data science focusing on the analysis of event data
generated during the execution of (business) processes, has seen a tremendous change …
generated during the execution of (business) processes, has seen a tremendous change …
[PDF][PDF] Predictive process monitoring
Predictive Process Monitoring [29] is a branch of process mining that aims at predicting the
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
[HTML][HTML] Utilizing domain knowledge in data-driven process discovery: A literature review
Process mining aims to improve operational processes in a data-driven manner. To this end,
process mining offers methods and techniques for systematically analyzing event data …
process mining offers methods and techniques for systematically analyzing event data …
[HTML][HTML] Business process variant analysis: Survey and classification
It is common for business processes to exhibit a high degree of internal heterogeneity, in the
sense that the executions of the process differ widely from each other due to contextual …
sense that the executions of the process differ widely from each other due to contextual …
Business process model merging: An approach to business process consolidation
This article addresses the problem of constructing consolidated business process models
out of collections of process models that share common fragments. The article considers the …
out of collections of process models that share common fragments. The article considers the …
Managing large collections of business process models—Current techniques and challenges
As it becomes increasingly common for organizations to work in a process-oriented manner,
single organizations may be dealing with collections of hundreds or thousands business …
single organizations may be dealing with collections of hundreds or thousands business …
Extracting event data from databases to unleash process mining
WMP Van der Aalst - BPM-Driving innovation in a digital world, 2015 - Springer
Increasingly organizations are using process mining to understand the way that operational
processes are executed. Process mining can be used to systematically drive innovation in a …
processes are executed. Process mining can be used to systematically drive innovation in a …
Process cubes: Slicing, dicing, rolling up and drilling down event data for process mining
WMP Van Der Aalst - Asia Pacific Business Process Management: First …, 2013 - Springer
Recent breakthroughs in process mining research make it possible to discover, analyze, and
improve business processes based on event data. The growth of event data provides many …
improve business processes based on event data. The growth of event data provides many …