维吾尔语和韩语形态分析之模型构建

为维吾尔语和韩语形态分析建立了一种图状结构的判别式模型，该模型将语句的形态分析建模为形态成分的图状结构，通过灵活丰富的特征设计描述了词语内部形态成分之间以及分属相邻词语的形态成分之间的关联约束.相比传统的线性模型，图状模型更好地考虑了各形态成分之间的语言学关联，从而取得更高的整句分析性能.在维吾尔语和韩语上的实验结果表明，图状模型相比线性模型的性能有一定提升，形态分析词级准确率分别提升了4.4%和2.8%.

Model Construction of Uygur and Korean Morphological Analysis

A discriminant model of the graphic structure is established for the morphological analysis of Uighur and Korean language. The model builds the morphological analysis of the sentence into the graphic structure of morphological components, and describes the correlation between the morphological components of the words inside and the morphological components of the adjacent words through flexible and rich feature design. Compared with the traditional linear model, the pattern model is better to consider the linguistic association between the morphological components, and it is expected to achieve higher sentence analysis performance. The experimental results in Uighur and Korean indicate that the graphic model achieves certain performance improvement comparing with the linear model, and the word level accuracy of morphological analysis respectively increases by 4.4 and 2.8 percentage points.