Web portals pioneered as one of the earliest adopters of personalization techniques to help users dealing with the problem of information overload. Nowadays they are extensively used as a single-point of access to the vast amount of resources available on the Web and in enterprise intranets. A number of researchers have been investigating the possibilities to enable portals to deliver the content in a highly-personalized manner in order to provide users with a quick and efficient access to the subset of resources relevant to their information needs. However, in order to achieve such a personalization effect, the portal needs accurate and up-to-date information about users, especially the information about their interests. In this paper, we describe a hybrid approach to identifying user interests in Web portals. In our approach, the portal is enabled to “learn” the user interests from the content of visited pages. In addition, it is empowered to provide users with an open access interface to their user models to let them explicitly specify their interests and, in case of incorrectly identified interests, outvote the portal.