Memory-Adaptative Dynamic Spatial Approximation Trees
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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.
KeywordsSearch Time Query Time Hybrid Index Distance Evaluation Insertion Algorithm
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