4 papers · 1 filter
A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri, Marcello La Rosa, Sarah M. Erfani
Event suffix and remaining time prediction are sequence to sequence learning tasks. They have wide applications in different areas such as economics, digital health, business proce…
Encoder-Decoder Generative Adversarial Nets for Suffix Generation and Remaining Time Prediction of Business Process Models
Farbod Taymouri, Marcello La Rosa
This paper proposes an encoder-decoder architecture grounded on Generative Adversarial Networks (GANs), that generates a sequence of activities and their timestamps in an end-to-en…
Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction
Farbod Taymouri, Marcello La Rosa, Sarah Erfani +2
Predictive process monitoring aims to predict future characteristics of an ongoing process case, such as case outcome or remaining timestamp. Recently, several predictive process m…
Business Process Variant Analysis based on Mutual Fingerprints of Event Logs
Farbod Taymouri, Marcello La Rosa, Josep Carmona
Comparing business process variants using event logs is a common use case in process mining. Existing techniques for process variant analysis detect statistically-significant diffe…