This paper proposes a pattern matching method applied to dictionaries to identify hierarchical relationships between terms. In this work we focus on this type of relationship because we use it in the automatic generation of thesauri, which are used to improve information retrieval tasks. However the method can also be applied to identify other semantic relationships. We distinguish two kinds of patterns: structural patterns, composed of a sequence of part-of-speech tags, and key patterns, typical of dictionary entries, composed of some key terms, along with some part-of-speech tags. This kind of patterns are automatically extracted for the dictionary entries by means of stochastic techniques. The thesaurus, that has been partially constructed previously, is then extended with the new relationships obtained by applying the patterns to a dictionary. We have based the system evaluation on the results obtained with and without the thesaurus in an information retrieval task proposed by the Cross-Language Evaluation Forum (CLEF). The results of these experiments have revealed a clear improvement on the performance.