电子科技大学学报2017，Vol.46Issue(6)：913-919,7.DOI:10.3969/j.issn.1001-0548.2017.06.021
自然语言处理中的深度学习:方法及应用
Deep Learning in NLP: Methods and Applications
摘要
Abstract
With the rise of deep learning waves, the full force of deep learning methods has hit the Natural Language Process (NLP) and ushered in amazing technological advances in many different application areas of NLP. In this article, we firstly present the development history, main advantages and research situation of deep learning. Secondly, in terms of both feature representation and model theory, we introduces the neural language model and word embedding as the entry point, and present an overview of modeling and implementations of Deep Neural Network (DNN). Then we focus on the newest deep learning models with their wonderful and competitive performances related to different NLP tasks. At last, we discuss and summarize the existing problems of deep learning in NLP with the possible future directions.关键词
深度学习/深度神经网络/语言模型/自然语言处理/词向量Key words
deep learning/deep neural networks/language models/nature language process/word embedding分类
信息技术与安全科学引用本文复制引用
林奕欧,雷航,李晓瑜,吴佳..自然语言处理中的深度学习:方法及应用[J].电子科技大学学报,2017,46(6):913-919,7.基金项目
国家自然科学基金(61502082) （61502082）
中央高校基本科研业务费(ZYGX2014J065) （ZYGX2014J065）
