  The technological evolution of the library in the academic environment
brought a lot of information and documents that are available to access, but
these systems do not always have mechanisms to search in an integrated way the
relevant information for the user. To alleviate this problem, we propose a
recommendation system that generates the user profile through tags that are
reshaped over time. To trace the user profile the system uses information from
your lending history stored in the library database and it collects their
opinions (feedback) through a list of recommendations. These data are
integrated with the document base of institutional repository.Thus, the
recommendation system assists users in identifying relevant items and makes
suggestions for content in an integrated environment that contains
institutional repository documents and the university library database. The
proposed recommendation system uses a hybrid approach being applied in an
academic environment with the participation of the users.
