LibShortText 是林智仁老师继 libsvm、liblinear 之后的另一力作，主要有几大特征：
- It is more efficient than general text-mining packages. On a typical computer, processing and training 10 million short texts takes only around half an hour.
- The fast training and testing is built upon the linear classifier LIBLINEAR
- Default options often work well without tedious tuning.
- An interactive tool for error analysis is included. Based on the property that each short text contains few words, LibShortText provides details in predicting each text.
这么一个工具，如何使用在中文处理呢？
尝试了一下中文的unigram feature的自动生成，发现中文character 没有count进unigram中=。=
于是我发信问了作者
作者回复：
Unfortunately I don't think our code can now support Chinese
documents.
Chih-Jen
但是，这完全是水平有限，对python不熟悉的后果，http://guoze.me/2014/09/25/libshorttext-introduction/ 这个链接里面，作者提出可以自己定制中文分词器来使程序work在中文上。