文本中最常见的 n 个单词

Question

I am currently learning to work with NLP. One of the problems I am facing is finding most common n words in text. Consider the following:

text=['Lion Monkey Elephant Weed','Tiger Elephant Lion Water Grass','Lion Weed Markov Elephant Monkey Fine','Guard Elephant Weed Fortune Wolf']

Suppose n = 2. I am not looking for most common bigrams. I am searching for 2-words that occur together the most in the text. Like, the output for the above should give:

'Lion' & 'Elephant': 3 'Elephant' & 'Weed': 3 'Lion' & 'Monkey': 2 'Elephant' & 'Monkey': 2

and such..

Could anyone suggest a suitable way to tackle this?

Answer 1

it was tricky but I solved for you, I used empty space to detect if elem contains more than 3 words:-) cause if elem has 3 words then it must be 2 empty spaces:-) in that case, only elem with 2 words will be returned

l = ["hello world", "good night world", "good morning sunshine", "wassap babe"]
for elem in l:

   if elem.count(" ") == 1:
      print(elem) 

output

hello world
wassap babe
  

Answer 2

I would suggest using Counter and combinations as follows.

from collections import Counter
from itertools import combinations, chain

text = ['Lion Monkey Elephant Weed', 'Tiger Elephant Lion Water Grass', 'Lion Weed Markov Elephant Monkey Fine', 'Guard Elephant Weed Fortune Wolf']


def count_combinations(text, n_words, n_most_common=None):
    count = []
    for t in text:
        words = t.split()
        combos = combinations(words, n_words)
        count.append([" & ".join(sorted(c)) for c in combos])
    return dict(Counter(sorted(list(chain(*count)))).most_common(n_most_common))

count_combinations(text, 2)