In this thesis, the main research is content-based junk short messages filtering which can be treated as irregular short text classification problem.
本文主要研究了基于内容的垃圾短信过滤，它可以看成是一个不规则短文本的分类问题。
The experimental results show that short-text classification performance can be improved by using the hyponymy.
实验表明：利用上下位关系能够改善短文本的分类性能。
Without training samples when using this method, we can get semantic information of ontology and combine the similarity calculations to achieve the short-text classification.
而且使用基于本体的短文本分类方法，无须训练样本，可以通过本体获得语义信息并结合相似性计算来实现对短文本的自动分类。
Without training samples when using this method, we can get semantic information of ontology and combine the similarity calculations to achieve the short-text classification.
而且使用基于本体的短文本分类方法，无须训练样本，可以通过本体获得语义信息并结合相似性计算来实现对短文本的自动分类。
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