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Motivated by decision support problems, data mining has been extensively addressed in the few past years. Nevertheless, the proposed approaches mainly concern flat representation of the data and to the best of our knowledge, not much effort has been spent on mining interesting patterns from such structures. In this paper we address the problem of mining structural association of semistructured data, or in other words the discovery of structural regularities among a large database of semistructured objects. This problem is much more complicated than the classical association rule one, since complex structures in the form of a labeled hirearchical objects partially ordered has to be taken into account.