Incremental Neighborhood Graphs Construction for Multidimensional Databases Indexing
Incremental Neighborhood Graphs Construction for Multidimensional Databases Indexing
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DOI：
10.1007/978-3-540-72665-4_35
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发表时间：
2007-05
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影响因子：
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通讯作者：
Hakim Hacid;Tetsuya Yoshida
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文献类型：
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作者：
Hakim Hacid;Tetsuya Yoshida
点定位（邻域搜索）是数据库和数据挖掘等领域的一个重要问题。邻域图是这个问题在多维空间中的有趣表示。然而，与邻域图相关的几个问题正在研究中，需要详细的工作来解决它们。这些问题主要与建筑成本高和更新困难有关。在这篇文章中，我们处理的点定位问题，考虑邻域图优化。我们提出并比较了两种能够快速构建和更新这些结构的策略。
The point location (neighborhood search) is a significant problem in several fields like databases and data mining. Neighborhood graphs are interesting representations of this problem in a multidimensional space. However, several problems related to neighborhood graphs are under research and require detailed work to solve them. These problems are mainly related to their high construction costs and to their updating difficulties. In this article, we deal with the point location problem by considering neighborhood graphs optimization. We propose and compare two strategies able to quickly build and update these structures.