Search Results for author:
Found 7 papers, 3 papers with code
Timeline-based Process Discovery
For that reason, it is surprising that current techniques for automatic process discovery generate directly-follows graphs and comparable process models, but often miss the opportunity to explicitly represent the time axis.
Knowledge-Driven Modulation of Neural Networks with Attention Mechanism for Next Activity Prediction
Predictive Process Monitoring (PPM) aims at leveraging historic process execution data to predict how ongoing executions will continue up to their completion.
Process Model Forecasting Using Time Series Analysis of Event Sequence Data
To this end, we develop a technique to forecast the entire process model from historical event data.
Conformance Checking of Mixed-paradigm Process Models
They are specifically interesting for process mining because they allow capturing complex behaviour in a compact way.
Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining
This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from information theory.
Comprehensive Process Drift Detection with Visual Analytics
The technique starts by clustering declarative process constraints discovered from recorded logs of executed business processes based on their similarity and then applies change point detection on the identified clusters to detect drifts.
Challenges and Opportunities of Applying Natural Language Processing in Business Process Management
The Business Process Management (BPM) field focuses in the coordination of labor so that organizational processes are smoothly executed in a way that products and services are properly delivered.
