A Web-Based Tool For Predictive Process Analytics
Name
Kerwin Jorbina
Abstract
Predictive Process Monitoring aims at exploiting event logs in business processes by providing predictions and forecasts on key business metrics such as time, cost and activity executions. As the interest in this field grows, various methods and approaches have been implemented in both academia and industry sectors in order to produce visual results that are understandable to the users. In this Master's Thesis, we propose a web-based framework and tool that enables participants in this field to build quick visualizations on their predictive models for evaluation. Furthermore, this project intends to have an independent front-end application which can work with any method running on the back-end as a web-service that is used in the prediction process. Finally, this project looks into the realm of inter-case predictions which uses multiple cases in building a prediction model of an event log.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Fabrizio Maria Maggi
Defence year
2017