基于语法语义信息量化模型的语素字再分类

Reclassifying Chinese Morpheme Word Based on Grammar and a Semantic Quantifiable Model

就语素字的再分类做了深入的研究,借鉴CLAWS算法,并在它的基础上引入了语义向量来辅助词性的自动标注。分析了语素字上下文中的标注的词性特点以及搭配词语来计算最有可能的语素字词性,实验表明该方法获得了较好的效果。

This paper presents a method of automatically retagging morpheme words using CLAWS (constituent-likelihood automatic word-tagging system) algorism with a semantic vector model. The context of morpheme words in reclassifying the different parts of speech is analyzed, the experiment shows that the method achieves the desired result.