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DBM-Tree: A Dynamic Metric Access Method Sensitive to Local Density Data

11 years 1 months ago
DBM-Tree: A Dynamic Metric Access Method Sensitive to Local Density Data
Metric Access Methods (MAM) are employed to accelerate the processing of similarity queries, such as the range and the k-nearest neighbor queries. Current methods improve the query performance minimizing the number of disk accesses, keeping a constant height of the structures stored on disks (height-balanced trees). The Slim-tree and the M-tree are the most efficient dynamic MAM so far. However, the overlapping between their nodes has a very high influence on their performance. This paper presents a new dynamic MAM called the DBM-tree (DensityBased Metric tree), which can minimize the overlap between high-density nodes by relaxing the height-balancing of the structure. Thus, the height of the tree is larger in denser regions, in order to keep a tradeoff between breadth-searching and depth-searching. Moreover, an optimization algorithm called Shrink is also presented, which improves the performance of an already built DBM-tree by reorganizing the elements among their nodes. Experiments...
Marcos R. Vieira, Caetano Traina Jr., Fabio Jun Ta
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where SBBD
Authors Marcos R. Vieira, Caetano Traina Jr., Fabio Jun Takada Chino, Agma J. M. Traina
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