Applying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data

Feiler, JanaWalter, TobiasMarkus Böhm, Jürgen Wunderlich2024-10-012024-10-012024978-3-88579-801-9https://dl.gi.de/handle/20.500.12116/44656Predictive Process Monitoring (PPM) is used to predict the future behavior of running process instances using machine learning techniques. While traditional PPM focuses and works well on highly structured business processes, the planned research explores the application of and challenges related to PPM on rather unstructured processes, such as those discovered through user click traces on websites. Therefore, this resarch’s overall objective is to develop and evaluate appropriate AI-supported PPM approaches for unstructured processes based on click traces provided by Germany’s public broadcaster ARD with its audio and video streaming services ARD Mediathek & ARD Audiothek.enProcess MiningPredictive Process MonitoringUnstructured Business ProcessesClick DataUser Behavior AnalysisApplying Predictive Process Monitoring to Predict User Behavior with Click Data Behavior with Click Data - Short PaperText/Conference Paper10.18420/AKWI2024-0171617-5468