散列相似性 [英] Hashing Similarity

问题描述

通常，哈希的目标是将一个连续的函数变成一个离散的函数：输入中的一个小的变化应该会导致输出的巨大变化。然而，是否有任何散列算法可以（大致）粗略地说为相似的输入返回相似但仍然不同的哈希值？

（使用这是通过检查两个文件的相似性来检查两个文件是否相似，当然，总是可以接受一些失败。）解析方案

查看局部敏感散列（LSH）。例如，这是一种快速找到特定点附近的点的概率方式。

Normally, the goal of hashing is to turn a continuous function into a discrete one: a small change in the input should cause a large change in the output. However, is there any hashing algorithm that will, (very) roughly speaking, return similar but (still different) hashes for similar inputs?

(An example of the use of this would be to check whether two files are "similar" by checking their hashes for similarity. Of course, some failure is always acceptable.)

解决方案

Look at Locality Sensitive Hashing (LSH). That is a probabilistic way of quickly finding a bunch of points near a given one, for example.

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