Using an Event Hierarchy for Improved Process Mining of Website User Behaviour

In the quest for improving systems, understanding user behaviour is a crucial step towards achieving optimal results. One technique that aids in comprehending user behaviour is process mining, which involves analysing event logs of a system. However, the accuracy of the process mining results can be impeded by large amounts of data or very unstructured processes, leading to confusion and difficulties in interpretation.To overcome this challenge, preprocessing techniques exist to enhance the resulting process maps. This work proposes a preprocessing method that utilizes an event hierarchy to produce a sanitized process map, that is easier to interpret.The proposed method involves analysing the event logs and creating a hierarchical structure of the events. This hierarchy allows the identification of relevant events and their corresponding dependencies, which in turn enables the extraction of useful process information.This preprocessing method has been tested on event data from an online newspaper, and it has shown promising results in improving readability of the resulting process maps. By utilizing an event hierarchy, relevant information can be extracted from large amounts of data and unstructured processes, leading to cleaner process maps that aid in understanding user behaviour.