Dynamic user modelling for personalised report generation of time-series data

The proposed work focuses on demonstrating how personal interests and preferences can be used to improve report gen- eration from time-series data. We apply these ideas in the weather and health informatics domains. In this extended abstract, we propose a dynamic User Model approach to data-driven generation that adds personalisation to the gen- erated reports. Our approach proposes that a User Model should be updated and in uenced from both user's traits and socially similar users taking into account the fact that these attributes may change over time. This is currently work in progress as part of a PhD by Dimitra Gkatzia and in connection with the Help4Mood project.