DIAGNOSIS AND PREDICTION OF BUSINESS PROCESS DEVIANCES
Grant number: DP180102839 | Funding period: 2018 - 2021
This project aims to develop an innovative approach based on process execution semantics, to analyse event data logged by IT systems in order to diagnose and predict business process deviance. Anticipated outcomes include novel business intelligence algorithms producing deviance diagnostics, predictions and recommendations and exposing results via interactive visual analytics. The outcomes are expected to aid process workers in steering business operations towards consistent and compliant outcomes and higher performance, and assist analysts and auditors to explain deviant operations. This should significantly benefit industries such as healthcare, insurance, retail and the government where c..View full description
Related publications (24)
Monotone Precision and Recall Measures for Comparing Executions and Specifications of Dynamic Systems
Artem Polyvyanyy, Andreas Solti, Matthias Weidlich, Claudio Di Ciccio, Jan Mendling
The behavioural comparison of systems is an important concern of software engineering research. For example, the areas of specific..
A Framework for Estimating Simplicity of Automatically Discovered Process Models Based on Structural and Behavioral Characteristics
Anna Kalenkova, Artem Polyvyanyy, Marcello La Rosa
A plethora of algorithms for automatically discovering process models from event logs has emerged. The discovered models are used ..
Automated Discovery of Data Transformations for Robotic Process Automation
Volodymyr Leno, Marlon Dumas, Marcello La Rosa, Fabrizio M Maggi, Artem Polyvyanyy
Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions w..
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
I Verenich, Marlon Dumas, M La Rosa, Fabrizio Maggi, Irene Teinemaa
Predictive business process monitoring methods exploit historical process execution logs to generate predictions about running ins..
Abstract and Compare: A Framework for Defining Precision Measures for Automated Process Discovery
A Augusto, A Armas Cervantes, R Conforti, M Dumas, M La Rosa, D Reissner
Automated process discovery techniques allow us to extract business process models from event logs. The quality of process models ..