围绕主题聚集短语
continue
I have encountered a very unusual problem. I have a set of phrases (noun phrases) extracted from a large corpus of documents. These phrases are >=2 and <=3 words of length. There is a need to cluster these phrases because the number of phrases extracted are very large in number and showing them as a simple list might not be useful for the user.
We are thinking of nice very simple ways of clustering these. Is there a quick tool/software/method that I could use to cluster these so that all phrases inside a cluster belong to a particular theme/topic, if I keep the number of topics as a fixed initially? I don't have any training set or any other clusters that I can use as a training set.
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主题分类不是一个简单的问题。
用于对长文档（数百个单词）进行分类的传统方法通常基于频繁出现的单词，并且不适合非常短的消息。我相信你的问题有点类似于推文分类。
两篇非常有趣的论文是：
（在 2011 年 HCI 国际上发表）
Topic classification is not an easy problem.
The conventional methods used to classify long documents (100's of words) are usually based on frequent words, and not suitable for very short messages. I believe that your problem is somewhat similar to tweet classification.
Two very interesting papers are:
(presented at HCI International 2011)
如果您想包含有关世界的知识，以便将猫和狗聚集在一起，您可以使用WordNet 的域层次结构。
If you want to include knowledge about the world so that, e.g., cat and dog will be clustered together, you can use WordNet's domains hierarchy.