We explore the acquisition of user profiles by unobtrusively monitoring the browsing behaviour of users by applying supervised machine-learning techniques coupled with an ontological representation to extract user preferences. The HIPRICE recommender system is presented and an empirical evaluation of this approach is conducted. The performance of the integrated systems is measured and presented as well.