  Ubiquitous information access becomes more and more important nowadays and
research is aimed at making it adapted to users. Our work consists in applying
machine learning techniques in order to adapt the information access provided
by ubiquitous systems to users when the system only knows the user social
group, without knowing anything about the user interest. The adaptation
procedures associate actions to perceived situations of the user. Associations
are based on feedback given by the user as a reaction to the behavior of the
system. Our method brings a solution to some of the problems concerning the
acceptance of the system by users when applying machine learning techniques to
systems at the beginning of the interaction between the system and the user.
