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首页> 外文会议>International Symposium on Web and Wireless Geographical Information Systems(W2GIS 2007); 20071128-29; Cardiff(GB) >Supporting Range Queries on Web Data Using k-Nearest Neighbor Search
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Supporting Range Queries on Web Data Using k-Nearest Neighbor Search

机译：使用k最近邻搜索在Web数据上支持范围查询

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摘要

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，网络上可以获取大量的地理空间数据。但是，由于受限的Web界面，某些类型的查询会限制对这些数据的访问。一个典型的场景是存在许多通过有限的“最近位置” Web界面提供其分支机构地址的商业网站。例如，可以查询连锁餐厅的网站，例如麦当劳，以查找其分支机构中与用户家庭住址最接近的位置。但是，即使该站点具有例如加利福尼亚州所有餐厅的位置数据，提供的Web界面也使得检索此数据集非常困难。通过仅利用k最近邻居（k-NN）查询，我们将此问题概念化为运行空间范围查询的更一般问题。随后，我们提出了两种算法，通过尽可能减少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算法的效率。

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