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Published Articles >> Table of Contents >> Abstract
21st International Conference on Data Engineering Workshops (ICDEW'05)
p. 1168
Efficient Evaluation of Radial Queries using the Target Tree
Michael D. Morse, Electrical Engineering and Computer Science University of Michigan
Jignesh M. Patel, Electrical Engineering and Computer Science University of Michigan
William I. Grosky, Dept. of Computer Science University of Michigan-Dearborn
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.214
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| Abstract |
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In this paper, we propose a novel indexing structure,
called the target tree, which is designed to efficiently
answer a new type of spatial query, called a radial query.
A radial query seeks to find all objects in the spatial data
set that intersect with line segments emanating from a
single, designated target point. Many existing and
emerging biomedical applications use radial queries,
including surgical planning in neurosurgery. Traditional
spatial indexing structures such as the R*-tree and
quadtree perform poorly on such radial queries. A target
tree uses a regular hierarchical decomposition of space
using wedge shapes that emanate from the target point,
resulting in an index structure that is very efficient for
evaluating radial queries. We present a detailed
performance evaluation of the target tree, comparing with
the R*-tree and quadtree indexing methods, and show
that the target tree method outperforms these existing
methods by at least a factor of 2-10.
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 Additional Information
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Citation:
Michael D. Morse, Jignesh M. Patel, William I. Grosky,
"Efficient Evaluation of Radial Queries using the Target Tree,"
icdew,
p. 1168,
21st International Conference on Data Engineering Workshops (ICDEW'05),
2005
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