This paper deals with the automatic retrieval of issues reported in legal texts and presents an experience with expert's reports on the application of ILO Conventions. The aim is to provide the end user, i.e. the legal expert, with a set of rules that permits her/him to find among a predefined list of issues those addressed by any new text. Since the end user is not supposed to be able to pre-process the text, we need rules that can be directly applied on raw texts. We present the strategy followed for generating the rules in this ILO legal setting and single out a few possible improvements that should significantly improve the performance of the retrieval process. Our approach consists in characterizing in a first stage a list of descriptor concepts, which are then used to get a quantitative representation of the texts. In the learning phase, using a sample of texts labeled by legal experts with the issues they actually address, we build the rules by means of induced decision trees.