如何在python中提高词移位距离相似度，并使用加权句子提供相似度评分

import nltk
from nltk.util import ngrams
from nltk.metrics.distance import edit_distance

def word_shift_distance(word1, word2):
    return edit_distance(word1, word2)

def weighted_sentence_similarity(sentence1, sentence2, weights):
    words1 = nltk.word_tokenize(sentence1)
    words2 = nltk.word_tokenize(sentence2)
    n = len(words1)
    m = len(words2)
    similarity = 0.0
    total_weight = 0.0

    for i in range(n):
        for j in range(m):
            distance = word_shift_distance(words1[i], words2[j])
            similarity += weights[i][j] * (1 - distance / max(len(words1[i]), len(words2[j])))
            total_weight += weights[i][j]

    if total_weight == 0:
        return 0.0

    return similarity / total_weight

weights = [[0.8, 0.2, 0.0],
           [0.2, 0.6, 0.2],
           [0.0, 0.2, 0.8]]

sentence1 = "This is a sample sentence."
sentence2 = "This is another example sentence."

similarity_score = weighted_sentence_similarity(sentence1, sentence2, weights)
print("Similarity Score:", similarity_score)