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JGTOOLS
2008

Proximity Cluster Trees

11 years 1 months ago
Proximity Cluster Trees
Hierarchical spatial data structures provide a means for organizing data for efficient processing. Most spatial data structures are optimized for performing queries, such as intersection and containment testing, on large data sets. Set-up time and complexity of these structures can limit their value for small data sets, an often overlooked yet important category in geometric processing. We present a new hierarchical spatial data structure, dubbed a proximity cluster tree, which is particularly effective on small data sets. Proximity cluster trees are simple to implement, require minimal construction overhead, and are structured for fast distance-based queries. Proximity cluster trees were tested on randomly generated sets of 2D B
Elena Jakubiak Hutchinson, Sarah F. Frisken, Ronal
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JGTOOLS
Authors Elena Jakubiak Hutchinson, Sarah F. Frisken, Ronald N. Perry
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