This paper describes how a user modeling knowledge base for personalized TV servers can be generated starting from an analysis of lifestyles surveys. The aim of the research is the construction of well-designed stereotypes for generating adaptive electronic program guides (EPGs) which filter the information about TV events depending on the user’s interests.