In this paper we present a comparative study of re-ranking methods using user profiles in digital libraries which contain scientific articles. While most of present personalized search systems only use content-based methods to re-rank search results, in our work we use many different content-based and citation-based methods for this purpose. We also study many functions to combine scores computed by these methods. We conducted experiments on the test collection used in the INEX 2005 campaign to evaluate our strategies and received interesting results.