计算机工程与应用2019，Vol.55Issue(24)：159-163,5.DOI:10.3778/j.issn.1002-8331.1808-0385
基于转移的神经网络哈萨克语句法分析
Transition-Based Kazakh Parsing with Neural Network
摘要
Abstract
For purpose of improving the parsing accuracy of Kazakh and laying the foundation for natural language processing, it researches Kazakh parsing based on transfer, and uses an improved transition-based method to deal with the syntax tree and convert the syntax tree into an action sequence, this method is in-order traversal over syntactic trees. The neural network is used to construct the parser framework, and three long short-term memory are used to express the stack information, buffer information and action history information to train the model. According to the probability of predicting the sequence of action, the result of syntactic analysis is obtained. The accuracy of Kazakh parsing obtained by the improved transition-based method is 74.37%.关键词
句法分析/转移方法/长短期记忆网络(LSTM)Key words
parsing/transfer method/long short-term memory分类
信息技术与安全科学引用本文复制引用
白雅雯,古丽拉·阿东别克..基于转移的神经网络哈萨克语句法分析[J].计算机工程与应用,2019,55(24):159-163,5.基金项目
国家自然科学基金(No.61363062). （No.61363062）
