The extraction of process models from text refers to the problem of turning the information
contained in an unstructured textual process descriptions into a formal representation, ie, a …

Abstract Machine learning (ML) provides algorithms to create computer programs based on
data without explicitly programming them. In business process management (BPM), ML …

This literature review studies the field of automated process extraction, ie transforming
textual descriptions into structured processes using Natural Language Processing (NLP) …

Automatic extraction of procedural graphs from documents creates a low-cost way for users
to easily understand a complex procedure by skimming visual graphs. Despite the progress …

Machine-learning based generation of process models from natural language text process
descriptions provides a solution for the time-intensive and expensive process discovery …

Workflow technology is a hot topic in the field of service computing. Due to the traditional
imperative business process models tending toward strict sequential logic, they can not …

One of the main promises of process conformance is the opportunity to align normative
processes (ie how the process should behave) and event logs (ie how does the process …

Process discovery is a family of techniques that helps to comprehend processes from their
data footprints. Yet, as processes change over time so should their corresponding models …

Abstract Context: Traceability Links Recovery has been a topic of interest for many years,
resulting in techniques that perform traceability based on the linguistic clues of the software …

Process discovery is a family of techniques that helps to comprehend processes from their
data footprints. Yet, as processes change over time so should their corresponding models …