From af4edd7579e51b6cd2622aea5a708a386ff181bc Mon Sep 17 00:00:00 2001 From: Vitali Fedulov Date: Wed, 20 Mar 2024 22:51:11 +0100 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 7aaee77..9765f37 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ Search nearest neighbour vectors in n-dimensional space with hashes. There are no dependencies in this package. -The algorithm is based on the assumption that two real numbers can be considered equal within certain equality distance. Therefore quantization is applicable for comparison. To make sure points near or at quantization borders are also comparable, a vector can be discretized into more than one hash, as described [here](https://vitali-fedulov.github.io/similar.pictures/algorithm-for-hashing-high-dimensional-float-vectors.html) (also as [PDF](https://github.com/vitali-fedulov/research/blob/main/Algorithm%20for%20hashing%20float%20vectors.pdf)). +The algorithm is based on the assumption that two real numbers can be considered equal within certain equality distance. Then quantization is used for comparison. To make sure points near or at quantization borders are also comparable, a vector can be discretized into more than one hash, as described [here](https://vitali-fedulov.github.io/similar.pictures/algorithm-for-hashing-high-dimensional-float-vectors.html) (also as [PDF](https://github.com/vitali-fedulov/research/blob/main/Algorithm%20for%20hashing%20float%20vectors.pdf)). The method indirectly clusters given vectors by hypercubes.