CoveringLSH

R. Pagh
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引用次数: 3

摘要

我们考虑Hamming空间中位置敏感哈希函数的一种新构造,该构造在一定意义上保证对给定半径r内的每一对向量产生碰撞。这种构造是有效的,因为对于给定c>1,距离cr处向量之间的哈希碰撞的期望数量接近于没有覆盖保证的最佳数据独立LSH,即:Indyk和Motwani开创性的LSH构建(STOC ' 98)。当搜索半径不太大时,新构造的效率基本上与它们的边界匹配。,当cr = o(log (n)/ log log n)时,其中n为数据集中的点数;当cr = log (n)/k时,其中k为整数常数。一般来说,它在时间界的指数上最多相差一个因子ln (4)因此,在Hamming空间中,基于lsh的相似性搜索可以以很少或没有成本的效率避免假阴性问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CoveringLSH
We consider a new construction of locality-sensitive hash functions for Hamming space that is covering in the sense that is it guaranteed to produce a collision for every pair of vectors within a given radius r. The construction is efficient in the sense that the expected number of hash collisions between vectors at distance cr, for a given c>1, comes close to that of the best possible data independent LSH without the covering guarantee, namely, the seminal LSH construction of Indyk and Motwani (STOC’98). The efficiency of the new construction essentially matches their bound when the search radius is not too large—e.g., when cr = o(log (n)/ log log n), where n is the number of points in the dataset, and when cr = log (n)/k, where k is an integer constant. In general, it differs by at most a factor ln (4) in the exponent of the time bounds. As a consequence, LSH-based similarity search in Hamming space can avoid the problem of false negatives at little or no cost in efficiency.
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