问题描述
对于文本分析程序，我想分析文本中某些单词的同时出现.例如，我希望看到巴拉克"和奥巴马"一词比其他词更经常出现(即具有正相关).
For a text analysis program, I would like to analyze the co-occurrence of certain words in a text. For example, I would like to see that e.g. the words "Barack" and "Obama" appear more often together (i.e. have a positive correlation) than others.
这似乎并不那么困难.但是，老实说，我只知道如何计算两个数字之间的相关性，而不是如何计算文本中两个单词之间的相关性.
This does not seem to be that difficult. However, to be honest, I only know how to calculate the correlation between two numbers, but not between two words in a text.
- 我如何最好地解决这个问题?
- 如何计算单词之间的相关性?
我考虑使用条件概率，因为奥巴马比奥巴马更有可能.但是，我尝试解决的问题更为根本，并且不取决于单词的顺序
推荐答案
Ngram统计信息包(NSP)正是致力于这项任务.他们有在线论文，其中描述了他们使用的关联度量.我没有亲自使用过该软件包，因此无法评论其可靠性/要求.
The Ngram Statistics Package (NSP) is devoted precisely to this task. They have a paper online which describes the association measures they use. I haven't used the package myself, so I cannot comment on its reliability/requirements.
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