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[HTML][HTML] Ticket automation: An insight into current research with applications to multi-level classification scenarios
Modern service providers often have to deal with large amounts of customer requests, which
they need to act upon in a swift and effective manner to ensure adequate support is …
they need to act upon in a swift and effective manner to ensure adequate support is …
ProcessGAN: Supporting the creation of business process improvement ideas through generative machine learning
Business processes are a key driver of organizational success, which is why business
process improvement (BPI) is a central activity of business process management. Despite an …
process improvement (BPI) is a central activity of business process management. Despite an …
Darwin: An online deep learning approach to handle concept drifts in predictive process monitoring
Predictive process monitoring (PPM) is a specific task under the umbrella of Process Mining
that aims to predict several factors of a business process (eg, next activity prediction) based …
that aims to predict several factors of a business process (eg, next activity prediction) based …
Decay replay mining to predict next process events
In complex processes, various events can happen in different sequences. The prediction of
the next event given an a-priori process state is of importance in such processes. Recent …
the next event given an a-priori process state is of importance in such processes. Recent …
Global conformance checking measures using shallow representation and deep learning
Conformance checking refers to techniques that can compare normative process behavior,
typically captured by process models, and observed process behavior, usually captured in …
typically captured by process models, and observed process behavior, usually captured in …
Assessing the performance of remaining time prediction methods for business processes
The prediction of the remaining time for business processes is a major task in predictive
process monitoring (PPM). In the last years, various machine learning methods were …
process monitoring (PPM). In the last years, various machine learning methods were …
Lupin: A llm approach for activity suffix prediction in business process event logs
Forecasting future states of running process instances is one of the main challenges of
Predictive Process Monitoring (PPM). Several deep learning approaches have recently …
Predictive Process Monitoring (PPM). Several deep learning approaches have recently …
BenchIMP: A benchmark for quantitative evaluation of the incident management process assessment
In the current scenario, where cyber-incidents occur daily, an effective Incident Management
Process (IMP) and its assessment have assumed paramount significance. While …
Process (IMP) and its assessment have assumed paramount significance. While …
Remaining cycle time prediction with graph neural networks for predictive process monitoring
Predictive process monitoring is at the intersection of machine learning and process mining.
This subfield of process mining leverages historical data generated from process executions …
This subfield of process mining leverages historical data generated from process executions …
[PDF][PDF] PM4KNIME: process mining meets the KNIME analytics platform
Process mining allows organizations to transform the data recorded during the execution of
their processes into meaningful insights. These insights can help to detect problems and to …
their processes into meaningful insights. These insights can help to detect problems and to …