Résumé: Process Mining focused only on the activity-oriented process and neglected the users' behaviors behind the activities, which led to overlooking the reality that they proposed to create. Recognizing the users' underlying intentions can improve the guidance and offer better recommendations. As a result, an area of study known as Intention Mining has been merged. It aims at discovering the users' behaviors using an event log. The intention is frequently used in different computer science research fields, including requirements definition, business process, and method engineering for context adaption. This paper reviews Intention-Oriented Process Mining based on event logs in the information systems engineering field. The objective is to identify the different models, methodologies, and algorithms proposed, the tools used, and the different challenges in these fields based on the four steps of review for the selection process, which start with the identification, followed by the screening, the eligibility, and the inclusion. For the first time, we are focused on Process Mining and intention mining based on log files and their relationship to get an idea about the area of intention mining. This paper reviews academic papers that are published in peer-reviewed venues from 2013 to 2022. These papers were examined through six main investigate questions and a systematic review. Also, we detailed the existing approaches in the Intention Mining area and present our comparative study. The results of the existing approaches indicate that Intention Mining shows a meaningful trace of research and creates existing opportunities for real technical applications.

Langue: Anglais