摘要
针对当前对文本情感分类任务的应用研究相对较少的问题,设计实现了一种利用Django框架实现的简易文本情感分类系统。后端主要使用双向长短时记忆(BiLSTM)网络结合自注意力机制构建的模型对文本进行情感分类,前端主要是由HTML,CSS,JQuery等实现。经过测试,可以较好地实现系统对输入文本的情感分类结果。
Aiming at the problem of relatively little research on text emotion classification task,a simple text emotion classification system based on Django framework is designed and implemented.The back end mainly uses bidirectional long and short-term menory(BiLSTM)network and the model built by self-attention mechanism to classify the text.The front end is mainly implemented by HTML,CSS,JQuery,and so on.Through testing,the system can achieve the result of emotion classification of input text.
作者
谢思雅
施一萍
胡佳玲
陈藩
刘瑾
XIE Siya;SHI Yiping;HU Jialing;CHEN Fan;LIU Jin(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《传感器与微系统》
CSCD
北大核心
2021年第11期97-99,共3页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(61701296)。
关键词
Django框架
双向长短时记忆网络
自注意力机制
情感分类
Django framework
bidirectional long and short-term menory(BiLSTM)network
self-attention mechanism
emotion classification
