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 …
Outcome-oriented predictive process monitoring: Review and benchmark
Predictive business process monitoring refers to the act of making predictions about the
future state of ongoing cases of a business process, based on their incomplete execution …
future state of ongoing cases of a business process, based on their incomplete execution …
Explainable concept drift in process mining
The execution of processes leaves trails of event data in information systems. These event
data are analyzed to generate insights and improvements for the underlying process …
data are analyzed to generate insights and improvements for the underlying process …
Detecting sudden and gradual drifts in business processes from execution traces
Business processes are prone to unexpected changes, as process workers may suddenly or
gradually start executing a process differently in order to adjust to changes in workload …
gradually start executing a process differently in order to adjust to changes in workload …
A framework for explainable concept drift detection in process mining
Rapidly changing business environments expose companies to high levels of uncertainty.
This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a …
This uncertainty manifests itself in significant changes that tend to occur over the lifetime of a …
Time-aware concept drift detection using the earth mover's distance
T Brockhoff, MS Uysal… - 2020 2nd International …, 2020 - ieeexplore.ieee.org
Modern business processes are embedded in a complex environment and, thus, subjected
to continuous changes. While current approaches focus on the control flow only, additional …
to continuous changes. While current approaches focus on the control flow only, additional …
Filtering spurious events from event streams of business processes
Process mining aims at gaining insights into business processes by analysing event data
recorded during process execution. The majority of existing process mining techniques …
recorded during process execution. The majority of existing process mining techniques …
Detecting process concept drifts from event logs
Traditional process discovery algorithms assume processes to be in a steady state.
However, process models tend to be dynamic due to various factors, which has brought …
However, process models tend to be dynamic due to various factors, which has brought …
Robust drift characterization from event streams of business processes
Process workers may vary the normal execution of a business process to adjust to changes
in their operational environment, eg, changes in workload, season, or regulations. Changes …
in their operational environment, eg, changes in workload, season, or regulations. Changes …
Concept drift detection and localization in process mining: An integrated and efficient approach enabled by trace clustering
Business processes are subject to changes over time due to the need for adaptation and
flexibility to a complex environment. Detecting drift as soon as possible and identifying the …
flexibility to a complex environment. Detecting drift as soon as possible and identifying the …