A Corpus of 21st Century Scots Texts

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Levenshtein Distance

Enter a word to find nearest neighbouring words, for example ahint

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Similar words to zbma in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
zbma (0) - 1 freq
zma (1) - 1 freq
ebka (2) - 1 freq
ba (2) - 140 freq
bra (2) - 31 freq
bza (2) - 1 freq
bmc (2) - 7 freq
mama (2) - 2 freq
za (2) - 3 freq
zjmp (2) - 1 freq
cbm (2) - 2 freq
bba (2) - 1 freq
zomb (2) - 1 freq
boa (2) - 16 freq
€˜ma (2) - 8 freq
rba (2) - 1 freq
bmw (2) - 4 freq
'bmv (2) - 1 freq
zeta (2) - 1 freq
o'ma (2) - 2 freq
zbji (2) - 1 freq
cama (2) - 1 freq
mdma (2) - 3 freq
zmf (2) - 1 freq
bmr (2) - 1 freq
zbma (0) - 1 freq
zma (2) - 1 freq
rbm (3) - 4 freq
cbm (3) - 2 freq
zm (3) - 1 freq
zebra (3) - 4 freq
zbji (3) - 1 freq
zbu (3) - 1 freq
zb (3) - 3 freq
ubmo (3) - 1 freq
zbqm (3) - 1 freq
obama (3) - 3 freq
bmi (3) - 1 freq
bm (3) - 5 freq
zara (4) - 3 freq
imma (4) - 1 freq
bmg (4) - 1 freq
hima (4) - 4 freq
puma (4) - 2 freq
alma (4) - 1 freq
fhma (4) - 1 freq
bmd (4) - 1 freq
pbya (4) - 1 freq
kbmf (4) - 1 freq
zlba (4) - 1 freq
SoundEx code - Z150
zephaniah - 3 freq
zczofm - 1 freq
zbma - 1 freq
MetaPhone code - SBM
zbma - 1 freq
ZBMA
Time to execute Levenshtein function - 0.208681 milliseconds
The Levenshtein distance is the number of characters you have to replace, insert or delete to transform one word into another, its useful for detecting typos and alternative spellings
Time to execute Double Levenshtein function - 0.369504 milliseconds
In a stroke of genius, this runs the Levenshtein function twice, once without vowels and adds the distance together, giving double weight to consonants.
Time to execute SoundEx function - 0.032015 milliseconds
Soundex is a phonetic algorithm for indexing names by sound, as pronounced in English. The goal is for homophones to be encoded to the same representation so that they can be matched despite minor differences in spelling.
Time to execute MetaPhone function - 0.040081 milliseconds
Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation.[1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
Time to execute Manually curated function - 0.000915 milliseconds
Manual Curation uses a lookup table / lexicon which has been created by hand which links words to their lemmas, and includes obvious typos and spelling variations. Not all words are covered.