Caverphone

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The Caverphone phonetic matching algorithm[1][2] was created by David Hood in the Caversham Project at the University of Otago in New Zealand in 2002, revised in 2004. It was created to assist in data matching between late 19th century and early 20th century electoral rolls, where the name only needed to be in a "commonly recognisable form". The algorithm was intended to apply to those names that could not easily be matched between electoral rolls, after the exact matches were removed from the pool of potential matches. The algorithm is optimised for accents present in the study area (southern part of the city of Dunedin, New Zealand).

The rules of the algorithm are applied consecutively to any particular name, as a series of replacements.

The exact algorithm is as follows:

  1. Convert to lowercase
  2. Remove anything not A-Z
  3. If the name starts with
    1. cough make it cou2f
    2. rough make it rou2f
    3. tough make it tou2f
    4. enough make it enou2f
    5. gn make it 2n
  4. If the name ends with
    1. mb make it m2
  5. Replace
    1. cq with 2q
    2. ci with si
    3. ce with se
    4. cy with sy
    5. tch with 2ch
    6. c with k
    7. q with k
    8. x with k
    9. v with f
    10. dg with 2g
    11. tio with sio
    12. tia with sia
    13. d with t
    14. ph with fh
    15. b with p
    16. sh with s2
    17. z with s
    18. any initial vowel with an A
    19. all other vowels with a 3
    20. 3gh3 with 3kh3
    21. gh with 22
    22. g with k
    23. groups of the letter s with a S
    24. groups of the letter t with a T
    25. groups of the letter p with a P
    26. groups of the letter k with a K
    27. groups of the letter f with a F
    28. groups of the letter m with a M
    29. groups of the letter n with a N
    30. w3 with W3
    31. wy with Wy
    32. wh3 with Wh3
    33. why with Why
    34. w with 2
    35. any initial h with an A
    36. all other occurrences of h with a 2
    37. r3 with R3
    38. ry with Ry
    39. r with 2
    40. l3 with L3
    41. ly with Ly
    42. l with 2
    43. j with y
    44. y3 with Y3
    45. y with 2
  6. remove all
    1. 2s
    2. 3s
  7. put six 1s on the end
  8. take the first six characters as the code

Examples[edit]

Lee -> lee
lee -> l33
l33 -> L33
L33 -> L
L -> L111111
L111111 -> L11111
Thompson -> thompson
thompson -> th3mps3n
th3mps3n -> th3mpS3n
th3mpS3n -> Th3mpS3n
Th3mpS3n -> Th3mPS3n
Th3mPS3n -> Th3MPS3n
Th3MPS3n -> Th3MPS3N
Th3MPS3N -> T23MPS3N
T23MPS3N ->  TMPSN
TMPSN111111 -> TMPSN1

See also[edit]

References[edit]

  1. ^ Milette, Greg; Stroud, Adam (2012-05-18). Professional Android Sensor Programming. John Wiley & Sons. pp. 421–. ISBN 9781118240458. Retrieved 19 February 2013. 
  2. ^ Phua, Clifton; Lee, Vincent; Smith, Kate (2006). "The Personal Name Problem And a Recommended Data Mining Solution". Encyclopedia of Data Warehousing and Mining. CiteSeerX: 10.1.1.127.5111. 

External links[edit]