| Levenshtein | Double Levenshtein | SoundEx | MetaPhone | Manually curated |
|---|---|---|---|---|
| name (0) - 1220 freq lame (1) - 10 freq came (1) - 899 freq naze (1) - 1 freq dame (1) - 16 freq nate (1) - 9 freq nave (1) - 1 freq kame (1) - 6 freq aname (1) - 1 freq nae (1) - 9872 freq namer (1) - 1 freq name' (1) - 3 freq nape (1) - 2 freq jame (1) - 3 freq names (1) - 304 freq mame (1) - 2 freq bame (1) - 2 freq nayme (1) - 2 freq naime (1) - 7 freq nme (1) - 2 freq rame (1) - 3 freq fame (1) - 48 freq hame (1) - 2346 freq same (1) - 1730 freq ame (1) - 3 freq |
name (0) - 1220 freq aname (1) - 1 freq nayme (1) - 2 freq nme (1) - 2 freq naime (1) - 7 freq named (2) - 53 freq eame (2) - 1 freq game (2) - 648 freq tame (2) - 23 freq nane (2) - 547 freq 'name (2) - 2 freq wame (2) - 75 freq nare (2) - 1 freq nemea (2) - 9 freq nm (2) - 2 freq nim (2) - 9 freq naim (2) - 5 freq naem (2) - 48 freq nymy (2) - 1 freq naomi (2) - 14 freq ame (2) - 3 freq nym (2) - 1 freq nom (2) - 2 freq nmo (2) - 1 freq nem (2) - 53 freq |
SoundEx code - N500 nane - 547 freq nae'n - 1 freq name - 1220 freq neen - 131 freq nem - 53 freq newin - 1 freq nuhin - 48 freq nine - 234 freq none - 57 freq naewan - 22 freq 'name - 2 freq noon - 29 freq non - 39 freq 'nemm - 2 freq na-na - 1 freq n'en - 6 freq nuin - 14 freq name' - 3 freq nan - 14 freq 'nane - 5 freq neem - 22 freq neon - 7 freq nanny - 7 freq naim - 5 freq neyn - 1 freq 'nuhin - 1 freq nuhin- - 1 freq nim - 9 freq nun - 10 freq nono - 1 freq nino - 1 freq naein - 1 freq naen - 10 freq naomh - 1 freq 'nine - 2 freq nein - 4 freq 'nein - 1 freq nimmo - 7 freq niné - 1 freq nen - 6 freq nain - 5 freq nahum - 3 freq 'no-no' - 1 freq numm - 1 freq naomi - 14 freq nannie - 4 freq nemm - 6 freq nyne - 4 freq naem - 48 freq nano- - 1 freq nemme - 9 freq non- - 1 freq nana - 11 freq nina - 1 freq naime - 7 freq nehm - 1 freq nummi - 3 freq nohin - 1 freq nemea - 9 freq noun - 48 freq neamh - 1 freq nayme - 2 freq 'none - 1 freq nönin - 1 freq €˜nannie - 1 freq naeyin - 2 freq €œnane - 3 freq nin - 1 freq naehin - 3 freq na'hin - 2 freq nom - 2 freq €˜name - 1 freq nehemiah - 1 freq nu'hin' - 5 freq neon- - 1 freq €œneen - 2 freq naun - 1 freq nuhin' - 1 freq niamh - 16 freq €˜niamh - 1 freq nien - 5 freq neean - 1 freq naamah - 2 freq no-one - 3 freq €™nine - 1 freq nihin - 5 freq neeenaaw - 1 freq niemi - 1 freq nean - 1 freq nani - 1 freq nyum - 2 freq nuhin” - 1 freq 'naan' - 1 freq naan - 2 freq nanna - 1 freq nyhn - 1 freq nymy - 1 freq nym - 1 freq nyummy - 1 freq |
MetaPhone code - NM name - 1220 freq nem - 53 freq 'name - 2 freq numb - 25 freq 'nemm - 2 freq gnome - 2 freq namby - 1 freq name' - 3 freq neem - 22 freq naim - 5 freq nim - 9 freq naomh - 1 freq nimmo - 7 freq numm - 1 freq naomi - 14 freq nemm - 6 freq naem - 48 freq nemme - 9 freq naime - 7 freq nehm - 1 freq nummi - 3 freq nemea - 9 freq neamh - 1 freq nayme - 2 freq ném - 1 freq nom - 2 freq €˜name - 1 freq niamh - 16 freq €˜niamh - 1 freq naamah - 2 freq nme - 2 freq niemi - 1 freq nm - 2 freq nmw - 1 freq gnom - 2 freq nymy - 1 freq nym - 1 freq nmo - 1 freq |
NAME name - 1220 freq named - 53 freq names - 304 freq naming - 2 freq |
| Time to execute Levenshtein function - 0.178208 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 - 0.338004 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 - 0.027998 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 - 0.036847 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 - 0.000925 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. |