Communication has never been more accessible than today. With the help
of Instant messengers and Email Services, millions of people can
transfer information with ease, and this trend has affected
organizations as well. There are billions of organizational emails sent
or received daily, and their main goal is to facilitate the daily
operation of organizations. Behind this vast corpus of human-generated
content, there is much implicit information that can be mined and used
to improve or optimize the organizations' operations. Business processes
are one of those implicit knowledge areas that can be discovered from
Email logs of an Organization, as most of the communications are
followed inside Emails. The purpose of this research is to propose an
approach to discover the process models in the Email log. In this
approach, we combine two tools, supervised machine learning and process
mining. With the help of supervised machine learning, fastText
classifier, we classify the body text of emails to the activity-related.
Then the generated log will be mined with process mining techniques to
find process models. We illustrate the approach with a case study
company from the oil and gas sector.