activity
20172024
most citedDetecting sudden and gradual drifts in business processes from execution traces

85 citations · 162 across the 12 of their papers we have counts for

collaborators

13 papers

cond-mat.mtrl-sci2024★ 38 cited

Certification Grade Quantum Dot Luminescent Solar Concentrator Glazing with Optical Communication Capability for Connected Sustainable Architecture

Francesco Meinardi, Francesco Bruni, Claudio Castellan +5

Energy sustainability and interconnectivity are the two main pillars on which cutting-edge architecture is based and require the realisation of energy and intelligent devices that…

econ.GN2023

Five guidelines to improve context-aware process selection: an Australian banking perspective

Nigel Adams, Adriano Augusto, Michael Davern +1

As the first phase in the Business Process Management (BPM) lifecycle, process identification addresses the problem of identifying which processes to prioritize for improvement. Pr…

cs.LG2023★ 2 cited

Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning

Zahra Dasht Bozorgi, Marlon Dumas, Marcello La Rosa +3

Increasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain…

cs.SE2021

Discovering executable routine specifications from user interaction logs

Volodymyr Leno, Adriano Augusto, Marlon Dumas +3

Robotic Process Automation (RPA) is a technology to automate routine work such as copying data across applications or filling in document templates using data from multiple applica…

cs.AI2021

Automated Repair of Process Models with Non-Local Constraints Using State-Based Region Theory

Anna Kalenkova, Josep Carmona, Artem Polyvyanyy +1

State-of-the-art process discovery methods construct free-choice process models from event logs. Consequently, the constructed models do not take into account indirect dependencies…

cs.LG2020★ 2 cited

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…

cs.AI2020★ 85 cited

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…

cs.SE2020

Efficient Conformance Checking using Approximate Alignment Computation with Tandem Repeats

Daniel Reißner, Abel Armas-Cervantes, Marcello La Rosa

Conformance checking encompasses a body of process mining techniques which aim to find and describe the differences between a process model capturing the expected process behavior…

cs.LG2019

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…

cs.PL2019★ 4 cited

Process Query Language: Design, Implementation, and Evaluation

Artem Polyvyanyy, Arthur H. M. ter Hofstede, Marcello La Rosa +2

Organizations can benefit from the use of practices, techniques, and tools from the area of business process management. Through the focus on processes, they create process models…

cs.AI2018★ 1 cited

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…

cs.LG2018

Discovering Process Maps from Event Streams

Volodymyr Leno, Abel Armas-Cervantes, Marlon Dumas +2

Automated process discovery is a class of process mining methods that allow analysts to extract business process models from event logs. Traditional process discovery methods extra…

cs.AI2017★ 30 cited

Outcome-Oriented Predictive Process Monitoring: Review and Benchmark

Irene Teinemaa, Marlon Dumas, Marcello La Rosa +1

Predictive business process monitoring refers to the act of making predictions about the future state of ongoing cases of a business process, based on their incomplete execution tr…