Incremental Reverse Nearest Neighbor Ranking
Incremental Reverse Nearest Neighbor Ranking
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DOI：
10.1109/icde.2009.144
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发表时间：
2009-03
期刊：
影响因子：
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通讯作者：
H. Kriegel;Peer Kröger;M. Renz;Andreas Züfle;Alexander Katzdobler
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文献类型：
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作者：
H. Kriegel;Peer Kröger;M. Renz;Andreas Züfle;Alexander Katzdobler
本文对增量式反向最近邻排序的新概念进行了形式化描述，并针对该问题提出了一种新颖的解决方案。我们提出了一种高效的方法来增量地报告结果，而不需要从头开始搜索。该方法适用于由任意R树索引结构分层组织的多维特征数据库。我们的解决方案不采用任何预处理步骤，这使得它适用于频繁更新数据库的动态环境。我们的实验表明，与已有的应用于排序问题的传统反向最近邻搜索方法相比，我们的方法以更少的页面访问来报告排序结果。
In this paper, we formalize the novel concept of incremental reverse nearest neighbor ranking and suggest an original solution for this problem. We propose an efficient approach for reporting the results incrementally without the need to restart the search from scratch. Our approach can be applied to a multi-dimensional feature database which is hierarchically organized by any R-tree like index structure. Our solution does not assume any preprocessing steps which makes it applicable for dynamic environments where updates of the database frequently occur. Our experiments show that our approach reports the ranking results with much less page accesses than existing approaches designed for traditional reverse nearest neighbor search applied to the ranking problem.