Process mining is a growing and promising study area focused on understanding processes
and to help capture the more significant findings during real execution rather than, those …

This paper explores and describes the state of the art for what concerns the model-driven
approaches proposed in the literature to support reverse engineering. We conducted a …

Currently, the process mining aims at an automatic extraction of process knowledge from the
event logs recorded by information systems, and, therefore, by using these techniques, it …

This research recognizes the limitation and challenges of adapting and applying Process
Mining as a powerful tool and technique in the Hypothetical Software Architecture (SA) …

Many present-day companies carry out a huge amount of daily operations through the use of
their information systems without ever having done their own enterprise modeling. Business …

Existing process mining methods are primarily designed for processes that have reached a
high degree of digitalization and standardization. In contrast, the literature has only begun to …

Process mining combines data mining with process analysis, eg to discover process models
from event logs. Practice shows that event logs grow very fast. Consequently, they quickly …

During the execution of software, tremendous amounts of data can be recorded. By
exploiting the execution data, one can discover behavioral models to describe the actual …

For many decades, process models have built the basis for economically successful
participation in the market. Companies are still faced with the task of identifying, defining and …

Understanding people's goals is a challenging issue that is met in many different areas such
as security, sales, information retrieval, etc. Intention Mining aims at uncovering intentions …