Continuous Visible Nearest Neighbour Queries

In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q, a CVNN query returns a set of (p, R) tuples such that p ? P is the nearest neighbor (NN) to every point r a...

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Main Authors: GAO, Yunjun, ZHENG, Baihua, LEE, Wang-Chien, CHEN, Gencai
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Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/sis_research/311
https://ink.library.smu.edu.sg/context/sis_research/article/1310/viewcontent/1516360.1516378.pdf
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spelling sg-smu-ink.sis_research-13102024-01-04T01:47:20Z Continuous Visible Nearest Neighbour Queries GAO, Yunjun ZHENG, Baihua LEE, Wang-Chien CHEN, Gencai In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q, a CVNN query returns a set of (p, R) tuples such that p ? P is the nearest neighbor (NN) to every point r along the interval R ? q as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R, due to the obstruction of some obstacles in O. In this paper, we formulate the problem and propose efficient algorithms for CVNN query processing, assuming that both P and O are indexed by R-trees. In addition, we extend our techniques to several variations of the CVNN query. Extensive experiments verify the efficiency and effectiveness of our proposed algorithms using both real and synthetic datasets. 2009-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/311 info:doi/10.1145/1516360.1516378 https://ink.library.smu.edu.sg/context/sis_research/article/1310/viewcontent/1516360.1516378.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Numerical Analysis and Scientific Computing
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Databases and Information Systems
Numerical Analysis and Scientific Computing
spellingShingle Databases and Information Systems
Numerical Analysis and Scientific Computing
GAO, Yunjun
ZHENG, Baihua
LEE, Wang-Chien
CHEN, Gencai
Continuous Visible Nearest Neighbour Queries
description In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q, a CVNN query returns a set of (p, R) tuples such that p ? P is the nearest neighbor (NN) to every point r along the interval R ? q as well as p is visible to r. Note that p may be NULL, meaning that all points in P are invisible to all points in R, due to the obstruction of some obstacles in O. In this paper, we formulate the problem and propose efficient algorithms for CVNN query processing, assuming that both P and O are indexed by R-trees. In addition, we extend our techniques to several variations of the CVNN query. Extensive experiments verify the efficiency and effectiveness of our proposed algorithms using both real and synthetic datasets.
format text
author GAO, Yunjun
ZHENG, Baihua
LEE, Wang-Chien
CHEN, Gencai
author_facet GAO, Yunjun
ZHENG, Baihua
LEE, Wang-Chien
CHEN, Gencai
author_sort GAO, Yunjun
title Continuous Visible Nearest Neighbour Queries
title_short Continuous Visible Nearest Neighbour Queries
title_full Continuous Visible Nearest Neighbour Queries
title_fullStr Continuous Visible Nearest Neighbour Queries
title_full_unstemmed Continuous Visible Nearest Neighbour Queries
title_sort continuous visible nearest neighbour queries
publisher Institutional Knowledge at Singapore Management University
publishDate 2009
url https://ink.library.smu.edu.sg/sis_research/311
https://ink.library.smu.edu.sg/context/sis_research/article/1310/viewcontent/1516360.1516378.pdf
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