Modelling User Behaviour based on Process

Search is designed primarily for human use, but we still lack efficient user models to evaluate search systems from the user's perspective. The purpose of this research is to identify user behaviour patterns during the search process, and develop a user model to illustrate the relationships between search behaviour and user perception, in order to predict user engagement in a cost-effective manner by using only behaviour data. To achieve this, we will use three datasets collected from previous studies containing both behavioural data from system log files and perception data. Ultimately, this research will yield a cost-efficient predictive model of user engagement that could be used to more effectively evaluate search systems.