首页> 外文会议>Pacific Asia Conference on Language, Information and Computation; 20061101-03; Wuhan(CN) >Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling
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Effective Tag Set Selection in Chinese Word Segmentation via Conditional Random Field Modeling

机译:通过条件随机场建模的中文分词中有效的标签集选择

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摘要

This paper is concerned with Chinese word segmentation, which is regarded as a character based tagging problem under conditional random field framework. It is different in our method that we consider both feature template selection and tag set selection, instead of feature template focused only method in existing work. Thus, there comes an empirical comparison study of performance among different tag sets in this paper. We show that there is a significant performance difference as different tag sets are selected. Based on the proposed method, our system gives the state-of-the-art performance.
机译:本文关注的是中文分词,它被视为条件随机场框架下基于字符的标签问题。在我们的方法中,我们既考虑要素模板选择又考虑标签集选择,而不是在现有工作中只关注要素模板。因此,本文对不同标签集之间的性能进行了实证比较研究。我们显示,由于选择了不同的标签集,因此存在明显的性能差异。基于所提出的方法,我们的系统提供了最先进的性能。

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