Human name comparison: ways to approach this task

Question

I'm not a Natural Language Programming student, yet I know it's not trivial strcmp(n1,n2).

Here's what i've learned so far:

• comparing Personal Names can't be solved 100%
• there are ways to achieve certain degree of accuracy.
• the answer will be locale-specific, that's OK.

I'm not looking for spelling alternatives! The assumption is that the input's spelling is correct.

For example, all the names below can refer to the same person:

• Berry Tsakala
• Bernard Tsakala
• Berry J. Tsakala
• Tsakala, Berry

I'm trying to:

1. build (or copy) an algorithm which grades the relationship 2 input names
2. find an indexing method (for names in my database, for hash tables, etc.)

note: My task isn't about finding names in text, but to compare 2 names. e.g.

name_compare( "James Brown", "Brown, James", "en-US" ) ---> 99.0%

Answer 1

Soundex is sometimes used to compare similar names. It doesn't deal with first name/last name ordering, but you could probably just have your code look for the comma to solve that problem.

Answer 2

I used Tanimoto Coefficient for a quick (but not super) solution, in Python:

"""
Formula:
  Na = number of set A elements
  Nb = number of set B elements
  Nc = number of common items

  T = Nc / (Na + Nb - Nc)
"""
def tanimoto(a, b):
    c = [v for v in a if v in b]
    return float(len(c)) / (len(a)+len(b)-len(c))

def name_compare(name1, name2):
    return tanimoto(name1, name2)


>>> name_compare("James Brown", "Brown, James")
0.91666666666666663
>>> name_compare("Berry Tsakala", "Bernard Tsakala")
0.75
>>>

Edit: A link to a good and useful book.

Answer 3

Analyzing name order and the existence of middle names/initials is trivial, of course, so it looks like the real challenge is knowing common name alternatives. I doubt this can be done without using some sort of nickname lookup table. This list is a good starting point. It doesn't map Bernard to Berry, but it would probably catch the most common cases. Perhaps an even more exhaustive list can be found elsewhere, but I definitely think that a locale-specific lookup table is the way to go.

Answer 4

We've just been doing this sort of work non-stop lately and the approach we've taken is to have a look-up table or alias list. If you can discount misspellings/misheard/non-english names then the difficult part is taken away. In your examples we would assume that the first word and the last word are the forename and the surname. Anything in between would be discarded (middle names, initials). Berry and Bernard would be in the alias list - and when Tsakala did not match to Berry we would flip the word order around and then get the match.