Memory-adaptative dynamic spatial approximation trees. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 2857, pages 360-368, 2003. abstract bibtex 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.
@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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