@inproceedings{0142156677,
    abstract = "Dynamic spatial approximation trees (dsa-trees) are efficient data structures for searching metric spaces. However, using enough storage, pivoting schemes beat dsa-trees in any metric space. In this paper we combine both concepts in a data structure that enjoys the features of dsa-trees and that improves query time by making the best use of the available memory. We show experimentally that our data structure is competitive for searching metric spaces. © Springer-Verlag Berlin Heidelberg 2003.",
    year = "2003",
    title = "Memory-adaptative dynamic spatial approximation trees",
    volume = "2857",
    pages = "360-368",
    booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"
}

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