22 citations · 29 across the 11 of their papers we have counts for
11 papers
RedSage: A Cybersecurity Generalist LLM
Naufal Suryanto, Muzammal Naseer, Pengfei Li +5
Cybersecurity operations demand assistant LLMs that support diverse workflows without exposing sensitive data. Existing solutions either rely on proprietary APIs with privacy risks…
Leveraging Duration Pseudo-Embeddings in Multilevel LSTM and GCN Hypermodels for Outcome-Oriented PPM
Fang Wang, Paolo Ceravolo, Ernesto Damiani
Existing deep learning models for Predictive Process Monitoring (PPM) struggle with temporal irregularities, particularly stochastic event durations and overlapping timestamps, lim…
HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data
Fang Wang, Paolo Ceravolo, Ernesto Damiani
We propose HGCN(O), a self-tuning toolkit using Graph Convolutional Network (GCN) models for event sequence prediction. Featuring four GCN architectures (O-GCN, T-GCN, TP-GCN, TE-G…
Comprehensive Attribute Encoding and Dynamic LSTM HyperModels for Outcome Oriented Predictive Business Process Monitoring
Fang Wang, Paolo Ceravolo, Ernesto Damiani
Predictive Business Process Monitoring (PBPM) aims to forecast future outcomes of ongoing business processes. However, existing methods often lack flexibility to handle real-world…
HH4AI: A methodological Framework for AI Human Rights impact assessment under the EUAI ACT
Paolo Ceravolo, Ernesto Damiani, Maria Elisa D'Amico +10
This paper introduces the HH4AI Methodology, a structured approach to assessing the impact of AI systems on human rights, focusing on compliance with the EU AI Act and addressing t…
Tailoring Machine Learning for Process Mining
Paolo Ceravolo, Sylvio Barbon Junior, Ernesto Damiani +1
Machine learning models are routinely integrated into process mining pipelines to carry out tasks like data transformation, noise reduction, anomaly detection, classification, and…
CoSMo: a Framework to Instantiate Conditioned Process Simulation Models
Rafael S. Oyamada, Gabriel M. Tavares, Sylvio Barbon Junior +1
Process simulation is gaining attention for its ability to assess potential performance improvements and risks associated with business process changes. The existing literature pre…
Trace Encoding in Process Mining: a survey and benchmarking
Sylvio Barbon, Paolo Ceravolo, Rafael S. Oyamada +1
Encoding methods are employed across several process mining tasks, including predictive process monitoring, anomalous case detection, trace clustering, etc. These methods are usual…
Selecting Optimal Trace Clustering Pipelines with AutoML
Sylvio Barbon, Paolo Ceravolo, Ernesto Damiani +1
Trace clustering has been extensively used to preprocess event logs. By grouping similar behavior, these techniques guide the identification of sub-logs, producing more understanda…
Using Meta-learning to Recommend Process Discovery Methods
Sylvio Barbon, Paolo Ceravolo, Ernesto Damiani +1
Process discovery methods have obtained remarkable achievements in Process Mining, delivering comprehensible process models to enhance management capabilities. However, selecting t…
Quantify resilience enhancement of UTS through exploiting connect community and internet of everything emerging technologies
Emanuele Bellini, Paolo Ceravolo, Paolo Besi
This work aims at investigating and quantifying the Urban Transport System (UTS) resilience enhancement enabled by the adoption of emerging technology such as Internet of Everythin…