关键词: 长短期记忆网络, 序列标注, 窥视孔连接, 长距离依赖, 梯度截断, 中文分词

Abstract: Long Short-Term Memory network（LSTM） can capture potential long-distance dependencies and has been widely used in Chinese word segmentation models. In order to further improve the effect, the word segmentation model is rebuilt by peepholes（peephole connection） in the case of error forgetting the key information in the processing sequence because of the structure problem in the memory unit. To optimize long distance dependencies, gradient truncation and guided information flow regularization are used. Through the construction of word segmentation experiments on current popular data sets, the results show that the memory unit of the peephole connection is more effective than the original memory unit to obtain the contextual features of the characters to be classified, effectively improving the missing information of the LSTM part and enhancing the memory ability of the network. The performance of the model word segmentation is higher.

Key words: Long Short-Term Memory（LSTM）, sequence labeling, peephole connection, long-distance dependence, gradient truncation, Chinese word segmentation