  Automated generalisation has known important improvements these last few
years. However, an issue that still deserves more study concerns the automatic
evaluation of generalised data. Indeed, many automated generalisation systems
require the utilisation of an evaluation function to automatically assess
generalisation outcomes. In this paper, we propose a new approach dedicated to
the design of such a function. This approach allows an imperfectly defined
evaluation function to be revised through a man-machine dialogue. The user
gives its preferences to the system by comparing generalisation outcomes.
Machine Learning techniques are then used to improve the evaluation function.
An experiment carried out on buildings shows that our approach significantly
improves generalisation evaluation functions defined by users.
