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Spatial Range Querying for Gaussian-Based Imprecise Query Objects
http://hdl.handle.net/2237/12310
http://hdl.handle.net/2237/12310ebec5018-506e-4972-ab92-3879691b9458
名前 / ファイル | ライセンス | アクション |
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icde.pdf (309.6 kB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2009-10-29 | |||||
タイトル | ||||||
タイトル | Spatial Range Querying for Gaussian-Based Imprecise Query Objects | |||||
言語 | en | |||||
著者 |
Ishikawa, Yoshiharu
× Ishikawa, Yoshiharu× Iijima, Yuichi× Yu, Jeffrey Xu |
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アクセス権 | ||||||
アクセス権 | open access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||
権利 | ||||||
言語 | en | |||||
権利情報 | Copyright (c) 2009 IEEE. Reprinted from Proceedings of the International Conference on Data Engineering (ICDE 2009), 2009, pp. 676-687. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Nagoya University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | imprecise locations | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | spatial range queries | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Gaussian distributions | |||||
抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In sensor environments and moving robot applications, the position of an object is often known imprecisely because of measurement error and/or movement of the object. In this paper, we present query processing methods for spatial databases in which the position of the query object is imprecisely specified by a probability density function based on a Gaussian distribution. We define the notion of a probabilistic range query by extending the traditional notion of a spatial range query and present three strategies for query processing. Since the qualification probability evaluation of target objects requires numerical integration by a method such as the Monte Carlo method, reduction of the number of candidate objects that should be evaluated has a large impact on query performance. We compare three strategies and their combinations in terms of the experiments and evaluate their effectiveness. | |||||
言語 | en | |||||
出版者 | ||||||
出版者 | IEEE Computer Society Press | |||||
言語 | en | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
出版タイプ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
ISBN | ||||||
関連タイプ | isPartOf | |||||
識別子タイプ | ISBN | |||||
関連識別子 | 978-0-7695-3545-6 | |||||
書誌情報 |
en : Proceedings of the International Conference on Data Engineering (ICDE 2009) p. 676-687, 発行日 2009-03 |
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フォーマット | ||||||
値 | application/pdf | |||||
著者版フラグ | ||||||
値 | publisher | |||||
URI | ||||||
識別子 | http://hdl.handle.net/2237/12310 | |||||
識別子タイプ | HDL | |||||
URI | ||||||
識別子 | http://dx.doi.org/10.1109/ICDE.2009.93 | |||||
識別子タイプ | DOI |