Open AccessJournal Article
Memory-adaptative dynamic spatial approximation trees
18
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.
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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.
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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
Enlarging nodes to improve dynamic spatial approximation trees
Marcelo Barroso,Nora Susana Reyes,Rodrigo Paredes +2 more
- 18 Sep 2010
TL;DR: A new data structure for searching in metric spaces is proposed, based on the DSA--trees, which holds its virtues and takes advantage of element clusters, which are present in many metric spaces, and can also make better use of available memory to improve searches.
Efficient parallelization of spatial approximation trees
Mauricio Marin,Nora Susana Reyes +1 more
- 22 May 2005
TL;DR: This paper describes the parallelization of the Spatial Approximation Tree and proposes a method for load balancing the work performed by the processors, which is self-tuning and is able to dynamically follow changes in the work-load generated by user queries.
Range queries in natural language dictionaries with recursive lists of clusters
Margarida Mamede,Fernanda Barbosa +1 more
- 01 Jan 2007
TL;DR: RLC is the only data structure that always keeps its good performance, whether the space dimension is lower or higher, and whether the query radius is smaller or larger.
12
References
Searching in metric spaces
TL;DR: A unified view of all the known proposals to organize metric spaces, so as to be able to understand them under a common framework, and presents a quantitative definition of the elusive concept of "intrinsic dimensionality".
1.4K
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
Enlarging nodes to improve dynamic spatial approximation trees
Marcelo Barroso,Nora Susana Reyes,Rodrigo Paredes +2 more
- 18 Sep 2010
TL;DR: A new data structure for searching in metric spaces is proposed, based on the DSA--trees, which holds its virtues and takes advantage of element clusters, which are present in many metric spaces, and can also make better use of available memory to improve searches.
Efficient parallelization of spatial approximation trees
Mauricio Marin,Nora Susana Reyes +1 more
- 22 May 2005
TL;DR: This paper describes the parallelization of the Spatial Approximation Tree and proposes a method for load balancing the work performed by the processors, which is self-tuning and is able to dynamically follow changes in the work-load generated by user queries.