Edit distance
Technique
In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings are to one another, that is measured by counting the minimum number of operations required to transform one string into the other. Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question. In bioinformatics, it can be used to quantify the similarity of DNA sequences, which can be viewed as strings of the letters A, C, G and T.
Related work
- ask.chaipat.cc, the ask-me-anything site Key work Nov 2026
If the question as typed finds little, the page tries a spelling correction, using Damerau–Levenshtein edit distance against the site's own vocabulary.
- thealgorithm Jan 2025
Text and data: cosine similarity and edit distance. Machine learning: Pegasos, a fast method for training support-vector machines.
In the knowledge graph
Edit distance and the 2 things it is linked to. Open any dot for its page, or explore it in the full graph.
As data
Everything on this page is read from triples in the knowledge graph. These are the 3 it states about Edit distance, and 1 more its ontology implies; the console runs SPARQL over the whole graph, here in your browser.
@prefix id: <https://ask.chaipat.cc/id/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix cj: <https://ask.chaipat.cc/ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix schema: <https://schema.org/> . id:EditDistance a cj:Technique ; rdfs:label "Edit distance" ; schema:sameAs <https://en.wikipedia.org/wiki/Edit_distance> .