85 citations · 117 across the 13 of their papers we have counts for
6 papers · 1 filter
Prescriptive Process Monitoring Under Resource Constraints: A Reinforcement Learning Approach
Mahmoud Shoush, Marlon Dumas
Prescriptive process monitoring methods seek to optimize the performance of business processes by triggering interventions at runtime, thereby increasing the probability of positiv…
Discovering Generative Models from Event Logs: Data-driven Simulation vs Deep Learning
Manuel Camargo, Marlon Dumas, Oscar Gonzalez-Rojas
A generative model is a statistical model that is able to generate new data instances from previously observed ones. In the context of business processes, a generative model create…
Detecting sudden and gradual drifts in business processes from execution traces
Abderrahmane Maaradji, Marlon Dumas, Marcello La Rosa +1
Business processes are prone to unexpected changes, as process workers may suddenly or gradually start executing a process differently in order to adjust to changes in workload, se…
Automated Discovery of Data Transformations for Robotic Process Automation
Volodymyr Leno, Marlon Dumas, Marcello La Rosa +2
Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions with one or more applications. In order to fully ex…
Semantic DMN: Formalizing and Reasoning About Decisions in the Presence of Background Knowledge
Diego Calvanese, Marlon Dumas, Fabrizio Maria Maggi +1
The Decision Model and Notation (DMN) is a recent OMG standard for the elicitation and representation of decision models, and for managing their interconnection with business proce…
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
Ilya Verenich, Marlon Dumas, Marcello La Rosa +2
Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such…