In order to improve existent information retrieval systems there is a need to take into account the semantic information conveyed in the texts. In this talk different approaches to this problem will be discussed aiming to identify the main issues and some possible solutions. A special focus on a deep linguistic based approach developed in the Computer Science Department of the University of Évora, Portugal, will be done. In this approach sentences are parsed and represented by DRS - Discourse Representation Structures. Then, these structures are transformed to graphs and distance metrics between these graphs are calculated. The overall idea behind this approach is that graph distance metrics are good ways of modelling the semantic distance between sentences. This approach was already applied with promising results to several NLP tasks, such as, text IR systems, text classification, and sentence similarity, and, in the talk, some of the obtained results will be presented.