This PR adds the `bag_of_words` function to count the frequency of words
for evaluation.
**Testing**
```Python
from unstructured.cleaners.core import bag_of_words
string = "The dog loved the cat, but the cat loved the cow."
print(bag_of_words)
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Co-authored-by: Mallori Harrell <mallori@Malloris-MacBook-Pro.local>
Co-authored-by: Klaijan <klaijan@unstructured.io>
Co-authored-by: Shreya Nidadavolu <shreyanid9@gmail.com>
Co-authored-by: shreyanid <42684285+shreyanid@users.noreply.github.com>
**Executive Summary**
Adds function to calculate edit distance (Levenshtein distance) between
two strings. The function can return as: 1. score (similarity = 1 -
distance/source_len) 2. distance (raw levenshtein distance)
**Technical details**
- The `weights` param is set to default at (2,1,1) for (insertion,
deletion, substitution), meaning that we will penalize the insertion we
need to add from output (target) in comparison with the source
(reference). In other word, the missing extraction will be penalized
higher.
- The function takes in 2 strings in an assumption that both string are
already clean and concatenated (CCT)
**Important Note!**
Test case needs to be updated to use CCT once the function is ready. It
is now only tested the "functionality" of edit distance, not the edit
distance with CCT as its intended to be.
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Co-authored-by: cragwolfe <crag@unstructured.io>
