Human name comparison: ways to approach this task

language-agnostic, nlp

Solution

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.

Problem

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: - build (or copy) an algorithm which grades the relationship 2 input names - 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% ```

Original source