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Supporting Range Queries on Web Data Using k-Nearest Neighbor Search

机译:使用K-Collect邻邻搜索在Web数据上支持范围查询

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A large volume of geospatial data is available on the web through various forms of applications. However, access to these data is limited by certain types of queries due to restrictive web interfaces. A typical scenario is the existence of numerous business web sites that provide the address of their branch locations through a limited "nearest location" web interface. For example, a chain restaurant's web site such as McDonalds can be queried to find some of the closest locations of its branches to the user's home address. However, even though the site has the location data of all restaurants in, for example, the state of California, the provided web interface makes it very difficult to retrieve this data set. We conceptualize this problem as a more general problem of running spatial range queries by utilizing only k-Nearest Neighbor (k-NN) queries. Subsequently, we propose two algorithms to cover the rectangular spatial range query by minimizing the number of k-NN queries as possible. Finally, we evaluate the efficiency of our algorithms through empirical experiments.
机译:通过各种形式的应用程序在网上提供大量的地理空间数据。但是,由于限制性的Web接口,对这些数据的访问受到某些类型的查询的限制。典型的方案是存在许多业务网站,通过有限的“最近的位置”Web界面提供分支位置的地址。例如,可以查询一个链式餐厅的网站,例如麦当劳,以查找其分支机构的一些最近的位置到用户的家庭地址。然而,即使该网站拥有所有餐馆的位置数据,例如,加利福尼亚州的状态,所提供的Web界面使得可以难以检索该数据集。我们将此问题概括为通过仅利用仅利用k最近邻(k-nn)查询来运行空间范围查询的更一般性问题。随后,我们提出了两种算法来覆盖尽可能最小化K-NN查询的数量来覆盖矩形空间范围查询。最后,我们通过经验实验评估我们算法的效率。

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