Abstract
We propose a computational model to synthesise individual-level user profiles from scarce population-level data in tourism domain. Namely, our model exploits, as input, summary information about the items (and item attributes) selected by users, and, as output, builds individual-level user profiles that respect the provided input. As a key contribution, we utilise discrete choice behavioural model to conjoin (via chi-square divergence minimisation) the choices made by the synthesised population of users with the choices observed in the real data. To showcase our idea, we release a code and a dataset that includes synthesised profiles of 10,000 users that interacted with circa 200 items.