摘要：Many computational applications need to look for informa-tion in a database. Nowadays, the predominance of non-conventional databases makes the similarity search (i.e.,searching elements of the database that are "similar" to agiven query) becomes a preponderant concept.The Spatial Approximation Tree has been shown that itcompares favorably against alternative data structures forsimilarity searching in metric spaces of medium to high di-mensionality ("difficult" spaces) or queries with low selec-tivity. However, for the construction process the tree roothas been randomly selected and the tree ,in its shape andperformance, is completely determined by this selection.Therefore, we are interested in improve mainly the searchesin this data structure trying to select the tree root so to re-.ect some of the own characteristics of the metric space tobe indexed. We regard that selecting the root in this way itallows a better adaption of the data structure to the intrin-sic dimensionality of the metric space considered, so also itachieves more efficient similarity searches
