不需要搜索的所有近邻图

Edgar Chávez, Verónica Ludueña, Nora Reyes, Fernando Kasián
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引用次数: 2

摘要

给定一个带有距离函数(·,·)的对象集合,最近邻图(NNG)就是找到集合中每个对象的最近邻居。在没有指标的情况下,NNG的总成本是二次的。如果单个项目的搜索是次线性的,那么使用索引的成本将是次二次的。不幸的是,由于所谓的维度诅咒,索引方法和蛮力方法几乎同样低效。在本文中,我们提出了一个有效的算法来构建近邻图(nNG),这是一个近似的nNG,只使用索引构建,而不实际搜索对象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
All Near Neighbor GraphWithout Searching
Given a collection ofnobjects equipped with a dis-tance functiond(·,·), the Nearest Neighbor Graph(NNG) consists in finding the nearest neighbor ofeach object in the collection. Without an index thetotal cost of NNG is quadratic. Using an index thecost would be sub-quadratic if the search for indi-vidual items is sublinear. Unfortunately, due to theso calledcurse of dimensionalitythe indexed and thebrute force methods are almost equally inefficient. Inthis paper we present an efficient algorithm to buildthe Near Neighbor Graph (nNG), that is an approx-imation of NNG, using only the index construction,without actually searching for objects.
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