利用覆盖歧义检测法和统计语言模型进行汉语自动分词

AUTOMATIC SEGMENTATION OF CHINESE USING OVERLAYING AMBIGUITY EXAMINING METHOD AND STATISTICS LANGUAGE MODEL

该文探讨了利用覆盖歧义检测法和统计语言模型进行汉语自动分词的问题。采用了多次迭代的方法来进行汉语词层面统计语言模型的训练。该方法能够得到更优化的语言模型。该文详细介绍了统计语言模型的训练过程,给出了语言模型复杂度随迭代次数增加而减小的实验结果。还给出了在不同的统计语言模型阶数下切分正确率变化的情况,分析了切分正确率变化的原因。

In this paper, the question of Chinese automatic segmentation is discussed using overlaying ambiguity examining method and statistics language model. The multi-time iterative method is applied to train language model, which can produce a better model. The process of training language model is described in detail. The result shows that the perplexity of language model is reduced. The accuracy of segmentation changes with different language model and the reason is analyzed.