中南民族大学学报（自然科学版）2017，Vol.36Issue(1)：102-106,5.
一种基于特征嵌入神经网络的中文分词方法
An Approach for Chinese Word Segmentation Based on Feature Embedding Neural Network
摘要
Abstract
The feature weights are poorly estimated, because the number of parameters is much greater than the limited amount of training data under the traditional Chinese word segmentation model based on feature.To address above problem, this paper proposed an approach based on feature embedding neural network for Chinese word segmentation.The embedding method can reduce the dimensional of features because the model transforms features into low-dimensional real-valued vectors.In addition, in order to enhance performance of the model, we proposed a learning rate linear decay method.Finally, we studied the regularization method to enhance the generalization ability of the model.The experiment results showed that the model can improve the solving efficiency of Chinese word segmentation.关键词
中文分词/神经网络/特征嵌入Key words
Chinese word segmentation/neural network/feature embedding分类
信息技术与安全科学引用本文复制引用
王文涛,穆晓峰,王玲霞..一种基于特征嵌入神经网络的中文分词方法[J].中南民族大学学报（自然科学版）,2017,36(1):102-106,5.基金项目
国家民委教改项目(15013) （15013）
中南民族大学研究生创新基金资助项目(2016sycxjj199) （2016sycxjj199）
