<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Edit-Distance on Scholion</title><link>https://scholion.thluiz.com/tags/edit-distance/</link><description>Recent content in Edit-Distance on Scholion</description><generator>Hugo -- gohugo.io</generator><language>pt-BR</language><copyright>© 2026</copyright><lastBuildDate>Fri, 13 May 2016 14:57:12 -0300</lastBuildDate><atom:link href="https://scholion.thluiz.com/tags/edit-distance/index.xml" rel="self" type="application/rss+xml"/><item><title>How to Write a Spelling Corrector</title><link>https://scholion.thluiz.com/notes/how-to-write-a-spelling-corrector/</link><pubDate>Fri, 13 May 2016 14:57:12 -0300</pubDate><guid>https://scholion.thluiz.com/notes/how-to-write-a-spelling-corrector/</guid><description>The essay builds a toy spell corrector from a language model, an error model, and edit-distance search, then tests it and shows why better context, data, and error estimates are needed.</description></item><item><title>A Simplified Version of Google's Spell Checker</title><link>https://scholion.thluiz.com/notes/a-simplified-version-of-googles-spell-checker/</link><pubDate>Fri, 13 May 2016 14:55:25 -0300</pubDate><guid>https://scholion.thluiz.com/notes/a-simplified-version-of-googles-spell-checker/</guid><description>Peter Norvig explains a 20-line Python spell checker that uses word counts from a text file and edit distance to choose the most frequent correction. The post says the simple method solved more than 80% of test cases.</description></item></channel></rss>