A Corpus of 21st Century Scots Texts

Intro a b c d e f g h i j k l m n o p q r s t u v w x y z Texts Writers Statistics Top200 Search Compare

Levenshtein Distance

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

- basic concord - pre-sorted concord - post-sorted concord - map and chronology - chronogrid - fine-grain concord -

Similar words to territor in Corpus

Levenshtein Double Levenshtein SoundEx MetaPhone Manually curated
territor (0) - 5 freq
territory (1) - 26 freq
territour (1) - 4 freq
terror (2) - 40 freq
terrier (2) - 13 freq
servitor (2) - 2 freq
territury (2) - 1 freq
territoral (2) - 1 freq
traitor (2) - 7 freq
territours (2) - 2 freq
heritor (2) - 1 freq
herrit (3) - 1 freq
traictor (3) - 1 freq
forritfor (3) - 1 freq
lerrit (3) - 2 freq
terrile (3) - 1 freq
merrit (3) - 6 freq
kerrion (3) - 1 freq
terrific (3) - 2 freq
corridor (3) - 56 freq
servitors (3) - 1 freq
terrie (3) - 2 freq
merrier (3) - 4 freq
terribie (3) - 1 freq
ferrier (3) - 6 freq
territor (0) - 5 freq
territour (1) - 4 freq
territory (1) - 26 freq
territury (2) - 1 freq
traitor (3) - 7 freq
territours (3) - 2 freq
territoral (3) - 1 freq
terror (3) - 40 freq
terrier (3) - 13 freq
terrour (4) - 1 freq
tarrier (4) - 1 freq
territories (4) - 5 freq
territorial (4) - 5 freq
tractor (4) - 57 freq
trector (4) - 2 freq
heritor (4) - 1 freq
tertar (4) - 2 freq
servitor (4) - 2 freq
narrator (4) - 30 freq
traictor (4) - 1 freq
traditor (4) - 1 freq
terrors (5) - 3 freq
tetror (5) - 1 freq
warrior (5) - 27 freq
cerrier (5) - 1 freq
SoundEx code - T636
tortur - 3 freq
throuither - 27 freq
trader - 9 freq
traders - 5 freq
territory - 26 freq
territorial - 5 freq
tear-draps - 2 freq
torturous - 2 freq
trotter - 5 freq
trotters - 9 freq
torturt - 1 freq
three-tiered - 2 freq
tortured - 19 freq
torture - 21 freq
thordarson - 4 freq
tratour - 1 freq
tartare - 1 freq
traitorous - 2 freq
tear-drap - 1 freq
torturers - 2 freq
third-world - 1 freq
territour - 4 freq
tortered - 1 freq
throu-ither - 1 freq
traitor - 7 freq
traitors - 6 freq
thorture - 2 freq
twartree - 111 freq
twaartree - 3 freq
territoral - 1 freq
territor - 5 freq
twarterit - 1 freq
thortert - 1 freq
traeder - 1 freq
territury - 1 freq
tertiary - 4 freq
torturit - 1 freq
teardraps - 1 freq
tertar - 2 freq
torters - 1 freq
tortert - 1 freq
three-tier - 1 freq
three-thirty's - 1 freq
territories - 5 freq
throweither - 1 freq
thorter - 2 freq
third-year - 1 freq
trotternish - 4 freq
twarthree - 1 freq
torturin - 1 freq
tortures - 1 freq
tharatour - 1 freq
torter - 1 freq
tartars - 1 freq
territours - 2 freq
twarthry - 1 freq
Ítróttarfelag - 1 freq
trateur - 1 freq
traitoris - 1 freq
teardrop - 1 freq
theorder - 1 freq
'traitor' - 1 freq
torturing - 1 freq
MetaPhone code - TRTR
tortur - 3 freq
trader - 9 freq
territory - 26 freq
dreidour - 1 freq
trotter - 5 freq
torture - 21 freq
tratour - 1 freq
tartare - 1 freq
territour - 4 freq
traitor - 7 freq
deirdre - 13 freq
dear-a-dear - 1 freq
territor - 5 freq
traeder - 1 freq
territury - 1 freq
tertar - 2 freq
torter - 1 freq
trateur - 1 freq
'traitor' - 1 freq
TERRITOR
Time to execute Levenshtein function - 0.258000 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 - 0.450633 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 - 0.028048 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 - 0.037156 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 - 0.000917 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.