We study a document retrieval problem in the new framework where D text documents are organized in a category tree with a pre-defined number h of categories. This situation occurs e.g. with taxomonic trees in biology or subject classification systems for scientific literature. Given a string pattern p and a category (level in the category tree), we wish to efficiently retrieve the t categorical units containing this pattern and belonging to the category. We propose several efficient solutions for this problem. One of them uses n(log(1 + o(1)) + logD + O(h)) + O() bits of space and O(p + t) query time, where n is the total length of the documents,the size of the alphabet used in the documents andis the total number of nodes in the category tree. Another solution uses n(log(1+o(1))+O(logD))+O()+O(Dlog n) bits of space and O(p+t logD) query time. We finally propose other solutions which are more space-efficient at the expense of a slight increase in query time. 2012 ACM Subject Classification Theory of computation ! Pattern matching; Information systems ! Document representation; Information systems ! Information retrieval query processing; Theory of computation ! Data structures design and analysis.