Question

I have a list of strings as a query and a few hundrends of other lists of strings. I want to compare the query with every other list and extract a similarity score between them.

Example:

query = ["football", "basketball", "martial arts", "baseball"]

list1 = ["apple", "football", "basketball court"]

list2 = ["ball"]

list3 = ["martial-arts", "baseball", "banana", "food", "doctor"]

What I am doing now and I am not satisfied with the results is an absolute compare of them.

score = 0
for i in query:
   if i in list1:
      score += 1

score_of_list1 = score*100//len(list1)

I found a library that may help me fuzzywuzzy, but I was thinking if you have any other way to suggest.

Was it helpful?

Solution

If you're looking for a way to find similarity between strings, this SO question suggests Levenshtein distance as a method of doing so.

There is a solution ready, and it also exists in the Natural Language Tool Kit library.

The naive integration would be (I use random merely to have a result. It doesn't make sense obviously):

#!/usr/bin/env python
query = ["football", "basketball", "martial arts", "baseball"]
lists = [["apple", "football", "basketball court"], ["ball"], ["martial-arts", "baseball", "banana", "food", "doctor"]]
from random import random

def fake_levenshtein(word1, word2):
    return random()

def avg_list(l):
        return reduce(lambda x, y: x + y, l) / len(l)

for l in lists:
    score = []
    for w1 in l:
        for w2 in query:
            score.append(fake_levenshtein(w1, w2))
    print avg_list(score)

Good luck.

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