Alessandro Padella

dblp:335/9721 · DBLP profile ↗
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2ranked-venue papers in the field
1as first author
2since 2021 · last 2026
0009-0008-6399-9364ORCID · corroborated

Domains — venue-derived; a paper can count in several

Business Process & Enterprise Data · 2 (1 first)
YearPublicationVenuePosition
2026 Balancing KPIs Through Multi-objective Prescriptive Process Analytics
Ngoc-Diem Le, Andrei Buliga 0001, Massimiliano Ronzani, Alessandro Padella, Massimiliano de Leoni
CAiSE (1)4
2022 Explainable Process Prescriptive Analytics
abstract
Process-aware Recommender systems (PAR systems) are information systems that aim to monitor process executions, predict their outcome, and recommend effective interventions to have better ends. Recent literature puts forward proposals of PAR systems that return valuable, practical recommendations. However, recommendations without sensible explanations prevent process owners from feeling engaged in the decision process or understanding why these interventions should be carried out. Therefore, the risk of process owners do not trust the PAR system and overlook these recommendations is high. This paper proposes a framework to accompany recommendations with sensible explanations based on the process behavior, the intrinsic characteristics, and the context in which the process is carried on. The paper illustrates the potential relevance of these explanations for process owners in two use cases.
Alessandro Padella, Massimiliano de Leoni, Onur Dogan 0001, Riccardo Galanti
ICPM1