使用NLTK比较术语/表达式的相似性? [英] Compare similarity of terms/expressions using NLTK?

问题描述

我正在尝试比较在语义上相关的术语/表达-这些不是完整的句子，不一定是单个单词；例如-

I'm trying to compare terms/expressions which would (or not) be semantically related - these are not full sentences, and not necessarily single words; e.g. -

社交网络服务"和社交网络"显然密切相关，但是我如何使用nltk对此进行量化?

'Social networking service' and 'Social network' are clearly strongly related, but how to i quantify this using nltk?

很明显，我甚至缺少一些代码:

Clearly i'm missing something as even the code:

w1 = wordnet.synsets('social network')

返回一个空列表.

有关如何解决此问题的任何建议?

Any advice on how to tackle this?

推荐答案

存在一些语义相关性或相似性的度量，但最好将它们定义为wordnet词典中的单个单词或单个表达式-而不是wordnet词典条目的复合词据我所知.

There are some measures of semantic relatedness or similarity, but they're better defined for single words or single expressions in wordnet's lexicon - not for compounds of wordnet's lexical entries, as far as I know.

这是一个很好的Web实现，其中包含许多基于wordnet的相似度度量

This is a nice web implementation of many similarity wordnet-based measures

• http://wn-similarity.sourceforge.net/

如果您有兴趣，还可以阅读一些有关使用词网相似性(尽管不评估化合物的相似性)来解释化合物的文章:

Some further reading on interpreting compounds using wordnet similarity (although not evaluating similarity on compounds), if you're interested:

• CiteSeerX (引用更为清晰)
• 同一文章，PDF

• CiteSeerX (citations are clearer)
• Same article, PDF

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