Visible Reverse K-Nearest Neighbor Queries
Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, data mining, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g.,...
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sg-smu-ink.sis_research-13082010-09-24T05:42:03Z Visible Reverse K-Nearest Neighbor Queries GAO, Yunjun ZHENG, Baihua CHEN, Gencai LEE, Wang-chien LEE, Ken C. K. LI, Qing Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, data mining, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings, blindages, etc.), and their presence may affect the visibility/distance between two objects. In this paper, we introduce a novel variant of RNN queries, namely visible reverse nearest neighbor (VRNN) search, which considers the obstacle influence on the visibility of objects. Given a data set P, an obstacle set O, and a query point q, a VRNN query retrieves the points in P that have q as their nearest neighbor and are visible to q. We propose an efficient algorithm for VRNN query processing, assuming that both P and O are indexed by R-trees. Our method does not require any pre-processing, and employs half-plane property and visibility check to prune the search space. 2009-04-01T07:00:00Z text https://ink.library.smu.edu.sg/sis_research/309 info:doi/10.1109/ICDE.2009.201 http://dx.doi.org/10.1109/ICDE.2009.201 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Databases and Information Systems Numerical Analysis and Scientific Computing |
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Databases and Information Systems Numerical Analysis and Scientific Computing GAO, Yunjun ZHENG, Baihua CHEN, Gencai LEE, Wang-chien LEE, Ken C. K. LI, Qing Visible Reverse K-Nearest Neighbor Queries |
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Reverse nearest neighbor (RNN) queries have a broad application base such as decision support, profile-based marketing, resource allocation, data mining, etc. Previous work on RNN search does not take obstacles into consideration. In the real world, however, there are many physical obstacles (e.g., buildings, blindages, etc.), and their presence may affect the visibility/distance between two objects. In this paper, we introduce a novel variant of RNN queries, namely visible reverse nearest neighbor (VRNN) search, which considers the obstacle influence on the visibility of objects. Given a data set P, an obstacle set O, and a query point q, a VRNN query retrieves the points in P that have q as their nearest neighbor and are visible to q. We propose an efficient algorithm for VRNN query processing, assuming that both P and O are indexed by R-trees. Our method does not require any pre-processing, and employs half-plane property and visibility check to prune the search space. |
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text |
author |
GAO, Yunjun ZHENG, Baihua CHEN, Gencai LEE, Wang-chien LEE, Ken C. K. LI, Qing |
author_facet |
GAO, Yunjun ZHENG, Baihua CHEN, Gencai LEE, Wang-chien LEE, Ken C. K. LI, Qing |
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GAO, Yunjun |
title |
Visible Reverse K-Nearest Neighbor Queries |
title_short |
Visible Reverse K-Nearest Neighbor Queries |
title_full |
Visible Reverse K-Nearest Neighbor Queries |
title_fullStr |
Visible Reverse K-Nearest Neighbor Queries |
title_full_unstemmed |
Visible Reverse K-Nearest Neighbor Queries |
title_sort |
visible reverse k-nearest neighbor queries |
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Institutional Knowledge at Singapore Management University |
publishDate |
2009 |
url |
https://ink.library.smu.edu.sg/sis_research/309 http://dx.doi.org/10.1109/ICDE.2009.201 |
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