问题描述
假设我有两个同义词集synset(car.n.01')和synset('bank.n.01')，如果我想在wordnet层次结构中找到这两个同义词集之间的距离，该如何使用nltk?
我在互联网上进行搜索，但是我得到了类似lin，resnik，jcn等的相似算法，这些算法无法解决我的问题.
请帮我解决这个问题.
Suppose I have two synsets synset(car.n.01') and synset('bank.n.01') and If I want to find the distance between these two synset in wordnet hierarchy then How can I do it using nltk?
I searched on internet but I am getting similarity algorithms like lin,resnik,jcn etc which are not solution for my question.
Please help me to solve this problem.
推荐答案
来自此
路径相似性，wup_similarity和lch_similarity ，所有这些都应该起作用，因为它们基于Wordnet层次结构中两个同义词集之间的距离.
Path similarity, wup_similarity and lch_similarity, all of these should work since they are based on the distance between two synsets in the Wordnet hierarchy.
dog = wn.synset('dog.n.01')
cat = wn.synset('cat.n.01')
dog.path_similarity(cat)
dog.lch_similarity(cat)
dog.wup_similarity(cat)
在同一链接中，(相关部分以粗体显示)
From the same link, (relevant portions in bold)
synset1.path_similarity(synset2):
synset1.lch_similarity(synset2)，Leacock-Chodorow相似度:
synset1.wup_similarity(synset2)，Wu-Palmer相似度:
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