Open Access
Fully dynamic and memory-adaptative spatial approximation trees
Diego Arroyuelo,Gonzalo Navarro,Nora Susana Reyes +2 more
- 01 Oct 2003
TL;DR: This paper completes and improves hybrid dynamic spatial approximation trees, by pre- senting a new search alternative, an algorithm to remove objects from the tree, and an improved way of managing the available memory.
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Abstract: Hybrid dynamic spatial approximation trees are recently proposed data structures for search- ing in metric spaces, based on combining the concepts of spatial approximation and pivot based algorithms. These data structures are hybrid schemes, with the full features of dynamic spatial approximation trees and able of using the available memory to improve the query time. It has been shown that they compare favorably against alternative data structures in spaces of medium difficulty. In this paper we complete and improve hybrid dynamic spatial approximation trees, by pre- senting a new search alternative, an algorithm to remove objects from the tree, and an improved way of managing the available memory. The result is a fully dynamic and optimized data structure for similarity searching in metric spaces.
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Citations
The Basic Principles of Metric Indexing
Magnus Lie Hetland
- 01 Jan 2009
TL;DR: This chapter describes several methods of similarity search, based on metric indexing, in terms of their common, underlying principles, and several approaches to creating lower bounds using the metric axioms are discussed.
•Journal Article
Fully dynamic Spatial Approximation Trees
TL;DR: In this article, the authors present a dynamic version of the SA-tree that handles insertions and deletions, showing experimentally that the price of adding dynamism is rather low.
39
•Posted Content
Ptolemaic Indexing
TL;DR: Ptolemy’s inequality holds for the well-known Euclidean distance, but is also shown here to hold for quadratic form metrics in general and the square root of any metric is Ptolemaic, which means that the principles introduced in this paper have a very wide applicability.
•Journal Article
Memory-adaptative dynamic spatial approximation trees
TL;DR: In this paper, the authors combine the features of dynamic spatial approximation trees (dsa-trees) and pivoting schemes in a data structure that improves query time by making the best use of the available memory.
18
References
Fully Dynamic Spatial Approximation Trees
Gonzalo Navarro,Nora Susana Reyes +1 more
- 11 Sep 2002
TL;DR: A dynamic version of the sa-tree that handles insertions and deletions is presented, showing experimentally that the price of adding dynamism is rather low and the outcome is a much more practical data structure that can be useful in a wide range of applications.
•Journal Article
Fully dynamic Spatial Approximation Trees
TL;DR: In this article, the authors present a dynamic version of the SA-tree that handles insertions and deletions, showing experimentally that the price of adding dynamism is rather low.
39
•Journal Article
Memory-adaptative dynamic spatial approximation trees
TL;DR: In this paper, the authors combine the features of dynamic spatial approximation trees (dsa-trees) and pivoting schemes in a data structure that improves query time by making the best use of the available memory.
18
Memory-adaptative dynamic spatial approximation trees
Diego Arroyuelo,Francisca Muñoz,Gonzalo Navarro,Nora Susana Reyes +3 more
- 08 Oct 2003
TL;DR: This paper combines dynamic spatial approximation trees and pivoting schemes 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.
Improved deletions in dynamic spatial approximation trees
Gonzalo Navarro,Nora Susana Reyes +1 more
- 06 Nov 2003
TL;DR: This paper proposes and study a new method to handle deletions over the dsa-tree, which is shown to be superior to the former in the sense that it does not affect search time at all and shows that the resulting tree is exactly as if the deleted element had never been inserted.
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