Chinese part of speech tagging based on maximum entropy method

Hong Ling, Chun-Fa Yuan
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引用次数: 6

Abstract

A lot of researches have been made on the application of the maximum entropy modeling in natural language processing in recent years. In this paper, we present a new Chinese part of speech tagging method based on the maximum entropy principle because Chinese language is quite different from many other languages. The feature selection is the key point in our system, which is distinct from the one used in English. Experiment results show that the part of speech tagging accuracy ratio of our system is up to 97.34%.
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基于最大熵法的汉语词性标注
近年来,人们对最大熵建模在自然语言处理中的应用进行了大量的研究。针对汉语与其他语言的巨大差异,本文提出了一种基于最大熵原理的汉语词性标注方法。特征选择是本系统的关键,它与英语中使用的特征选择不同。实验结果表明,该系统的词性标注准确率可达97.34%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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