IPMD: Intentional Process Model Discovery from Event Logs

被引:0
作者
Elali, Ramona [1 ]
Kornyshova, Elena [2 ]
Deneckere, Rebecca [1 ]
Salinesi, Camille [1 ]
机构
[1] Paris 1 Pantheon Sorbonne, Paris, France
[2] Conservatoire Natl Arts & Metiers, Paris, France
来源
RESEARCH CHALLENGES IN INFORMATION SCIENCE, PT II, RCIS 2024 | 2024年 / 514卷
关键词
Intention Mining; Intentional Process Model; Frequent Pattern Mining; Process Mining; Large Language Model;
D O I
10.1007/978-3-031-59468-7_5
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:38 / 46
页数:9
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