Abstract
Intention Mining is a crucial aspect of understanding human behavior. It focuses on uncovering the underlying hidden intentions and goals that guide individuals in their activities. We propose the approach IPMD (Intentional Process Model Discovery) that combines Frequent Pattern Mining, Large Language Model, and Process Mining to construct intentional process models that capture the human strategies inherited from his decision-making and activity execution. This combination aims to identify recurrent sequences of actions revealing the strategies (recurring patterns of activities), that users commonly apply to fulfill their intentions. These patterns are used to construct an intentional process model that follows the MAP formalism based on strategy discovery.
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Elali, R., Kornyshova, E., Deneckère, R., Salinesi, C. (2024). IPMD: Intentional Process Model Discovery from Event Logs. In: Araújo, J., de la Vara, J.L., Santos, M.Y., Assar, S. (eds) Research Challenges in Information Science. RCIS 2024. Lecture Notes in Business Information Processing, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-031-59468-7_5
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DOI: https://doi.org/10.1007/978-3-031-59468-7_5
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