A better similarity ranking algorithm for variable length strings

Question

I'm looking for a string similarity algorithm that yields better results on variable length strings than the ones that are usually suggested (levenshtein distance, soundex, etc).

For example,

Given string A: "Robert",

Then string B: "Amy Robertson"

would be a better match than

String C: "Richard"

Also, preferably, this algorithm should be language agnostic (also works in languages other than English).

Answer 1

Simon White of Catalysoft wrote an article about a very clever algorithm that compares adjacent character pairs that works really well for my purposes:

http://www.catalysoft.com/articles/StrikeAMatch.html

Simon has a Java version of the algorithm and below I wrote a PL/Ruby version of it (taken from the plain ruby version done in the related forum entry comment by Mark Wong-VanHaren) so that I can use it in my PostgreSQL queries:

CREATE FUNCTION string_similarity(str1 varchar, str2 varchar)
RETURNS float8 AS '

str1.downcase! 
pairs1 = (0..str1.length-2).collect {|i| str1[i,2]}.reject {
  |pair| pair.include? " "}
str2.downcase! 
pairs2 = (0..str2.length-2).collect {|i| str2[i,2]}.reject {
  |pair| pair.include? " "}
union = pairs1.size + pairs2.size 
intersection = 0 
pairs1.each do |p1| 
  0.upto(pairs2.size-1) do |i| 
    if p1 == pairs2[i] 
      intersection += 1 
      pairs2.slice!(i) 
      break 
    end 
  end 
end 
(2.0 * intersection) / union

' LANGUAGE 'plruby';

Works like a charm!