I need to compare strings to decide whether they represent the same thing. This relates to case titles entered by humans where abbreviations and other small details may di
What you're looking for are called String Metric algorithms. There a significant number of them, many with similar characteristics. Among the more popular:
Have a look at these as well as others on the wiki page on the topic.
You may use the algorithm of computing the length of the longest common sub-sequence to solve the problem. If the length of the longest common sub-sequence for both the input strings is less than the length of either of the strings, they are unequal.
You may use the approach of dynamic programming to solve the problem and optimize the space complexity as well in case you don't wish to figure out the longest common sub-sequence.
Damerau Levenshtein distance is another algorithm for comparing two strings and it is similar to the Levenshtein distance algorithm. The difference between the two is that it can also check transpositions between characters and hence may give a better result for error correction.
For example: The Levenshtein distance between night
and nigth
is 2
but Damerau Levenshtein distance between night
and nigth
will be 1 because it is just a swap of a pair of characters.
Another algorithm that you can consider is the Simon White Similarity:
def get_bigrams(string):
"""
Take a string and return a list of bigrams.
"""
if string is None:
return ""
s = string.lower()
return [s[i : i + 2] for i in list(range(len(s) - 1))]
def simon_similarity(str1, str2):
"""
Perform bigram comparison between two strings
and return a percentage match in decimal form.
"""
pairs1 = get_bigrams(str1)
pairs2 = get_bigrams(str2)
union = len(pairs1) + len(pairs2)
if union == 0 or union is None:
return 0
hit_count = 0
for x in pairs1:
for y in pairs2:
if x == y:
hit_count += 1
break
return (2.0 * hit_count) / union
You could use ngrams for that. For example, transform the two strings in word trigrams (usually lowercase) and compare the percentage of them that are equal to one another.
Your challenge is to define a minimum percentage for similarity.
http://en.wikipedia.org/wiki/N-gram