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Predicting the completion time of business process instances would be a very helpful aid when managing processes under service level agreement constraints. The ability to know in advance the trend of running process instances would allow…

Machine Learning · Computer Science 2017-11-13 Nicolò Navarin , Beatrice Vincenzi , Mirko Polato , Alessandro Sperduti

Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running instances (called cases) of a business process, such as the prediction of the outcome, next activity or remaining…

Artificial Intelligence · Computer Science 2018-05-14 Ilya Verenich , Marlon Dumas , Marcello La Rosa , Fabrizio Maggi , Irene Teinemaa

Predictive process monitoring supports operational decision-making by forecasting future states of ongoing business cases. A key task is case suffix prediction, which estimates the remaining sequence of activities for a case. Most existing…

Machine Learning · Computer Science 2026-04-23 Muhammad Awais Ali , Marlon Dumas , Fredrik Milani

Process analytics is an umbrella of data-driven techniques which includes making predictions for individual process instances or overall process models. At the instance level, various novel techniques have been recently devised, tackling…

Machine Learning · Computer Science 2021-07-29 Johannes De Smedt , Anton Yeshchenko , Artem Polyvyanyy , Jochen De Weerdt , Jan Mendling

Process analytics approaches allow organizations to support the practice of Business Process Management and continuous improvement by leveraging all process-related data to extract knowledge, improve process performance and support…

Other Computer Science · Computer Science 2025-02-25 Asjad Khan , Aditya Ghose , Hoa Dam , Arsal Syed

Numerous powerful point process models have been developed to understand temporal patterns in sequential data from fields such as health-care, electronic commerce, social networks, and natural disaster forecasting. In this paper, we develop…

Computer Vision and Pattern Recognition · Computer Science 2018-08-15 Yatao Zhong , Bicheng Xu , Guang-Tong Zhou , Luke Bornn , Greg Mori

Predictive business process monitoring methods exploit logs of completed cases of a process in order to make predictions about running cases thereof. Existing methods in this space are tailor-made for specific prediction tasks. Moreover,…

Applications · Statistics 2017-12-20 Niek Tax , Ilya Verenich , Marcello La Rosa , Marlon Dumas

Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, most of the…

Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs).…

Artificial Intelligence · Computer Science 2018-07-03 Ario Santoso

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 traces and logs of historical (completed) traces. Motivated by…

Artificial Intelligence · Computer Science 2018-10-24 Irene Teinemaa , Marlon Dumas , Marcello La Rosa , Fabrizio Maria Maggi

Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process instances. Such predictions are of significant interest to the process stakeholders. However, state-of-the-art…

Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs).…

Artificial Intelligence · Computer Science 2019-04-25 Ario Santoso , Michael Felderer

Perhaps surprisingly, it is possible to predict how long an algorithm will take to run on a previously unseen input, using machine learning techniques to build a model of the algorithm's runtime as a function of problem-specific instance…

Artificial Intelligence · Computer Science 2013-10-29 Frank Hutter , Lin Xu , Holger H. Hoos , Kevin Leyton-Brown

A characteristic of existing predictive process monitoring techniques is to first construct a predictive model based on past process executions, and then use it to predict the future of new ongoing cases, without the possibility of updating…

Artificial Intelligence · Computer Science 2023-10-26 Chiara Di Francescomarino , Chiara Ghidini , Fabrizio Maria Maggi , Williams Rizzi , Cosimo Damiano Persia

Predictive business process monitoring is concerned with the prediction how a running process instance will unfold up to its completion at runtime. Most of the proposed approaches rely on a wide number of different machine learning (ML)…

Artificial Intelligence · Computer Science 2021-04-21 Martin Käppel , Stefan Jablonski , Stefan Schönig

Process variant analysis aims at identifying and addressing the differences existing in a set of process executions enacted by the same process model. A process model can be executed differently in different situations for various reasons,…

Other Computer Science · Computer Science 2019-12-24 Farbod Taymouri , Marcello La Rosa , Marlon Dumas , Fabrizio Maria Maggi

Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's performance. A centerpiece of a prescriptive process monitoring…

Artificial Intelligence · Computer Science 2022-06-17 Mahmoud Shoush , Marlon Dumas

Business process simulation is an approach to evaluate business process changes prior to implementation. Existing methods in this field primarily support tactical decision-making, where simulations start from an empty state and aim to…

Software Engineering · Computer Science 2025-09-10 Maksym Avramenko , David Chapela-Campa , Marlon Dumas , Fredrik Milani

Predicting undesirable events during the execution of a business process instance provides the process participants with an opportunity to intervene and keep the process aligned with its goals. Few approaches for tackling this challenge…

Artificial Intelligence · Computer Science 2020-09-22 Jens Brunk , Matthias Stierle , Leon Papke , Kate Revoredo , Martin Matzner , Jörg Becker

A business process model represents the expected behavior of a set of process instances (cases). The process instances may be executed in parallel and may affect each other through data or resources. In particular, changes in values of data…

Software Engineering · Computer Science 2024-01-31 Yotam Evron , Arava Tsoury , Anna Zamansky , Iris Reinhartz-Berger , Pnina Soffer
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