<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Excels on Agent Arachnids Anthology</title><link>https://agentarachnid66.github.io/excel/</link><description>Recent content in Excels on Agent Arachnids Anthology</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Wed, 27 May 2026 00:59:01 +0100</lastBuildDate><atom:link href="https://agentarachnid66.github.io/excel/index.xml" rel="self" type="application/rss+xml"/><item><title>Levenshtein Distance and Excel</title><link>https://agentarachnid66.github.io/excel/lev_distance/</link><pubDate>Wed, 27 May 2026 00:59:01 +0100</pubDate><guid>https://agentarachnid66.github.io/excel/lev_distance/</guid><description>The Levenshtein Distance is a method of comparing two strings, via a recursive function that looks for 3 transformations, each one adds one to the total &amp;lsquo;distance&amp;rsquo;
This is very useful as a basic metric for comparing strings against a target. I&amp;rsquo;m aimimg to use it in my exploration of fuzzy string matching as a metric.
Transformations Overview Insertions If the source string has to add new characters to match the target string</description></item></channel></rss>