运用文本领域的常识改善基于支撑向量机的文本分类器性能

本文提出了一种提高中文文本分类器推广性能的方法。一般而言,采用机器学习的方法对文本集合进行训练,可以获得文本分类器。本文引入了文本语义不变性常识,并将其融合到文本分类器中,提出了改进文本分类器的方法。与支撑向量机相结合,设计并实现了改进的文本分类器。对中文文本分类的实验表明,文本语义不变性常识的运用有效地改善了分类器的推广性能。

Improving the Performance of the Text Classifier Based on Support Vector Machine Using the Common Sense in Text Domain

In the paper,a method to improve the generalization performance of the Chinese text classifier is put forward.Generally speaking,a text classifier is obtained by training text set with a machine learning method.A kind of common sense about text semantic invariance is introduced.A method to improve the text classifier is put forward by fusing the common sense into it.With the combination with a Support Vector Machine,we design and implement the improved text classifier.The experiment shows that the generalization performance of the text classifier is improved with the method.