摘要
现阶段有关人工智能在文本情感分析中的应用等相对研究较少,基于该问题现状,要求行之有效的措施对其进行分析研究,如以大数据模型为主、以深度识别为方向、以深度识别为方向、CNN架构设计及需求分析、实现及应用分析等。该研究对进行分析,有十分重要的理论意义。同时该研究是在CNN算法改进后,将其系统设计框架进行布局,并融合相关技术、算法等逐一完善。
At this stage,there are relatively few researches on the application of artificial intelligence in text sentiment analy⁃sis.Based on the current situation of the problem,effective measures are required to analyze and research it,such as focusing on big data models,focusing on deep recognition,and In-depth recognition is the direction,CNN architecture design and demand analysis,implementation and application analysis,etc.This research has very important theoretical significance for analysis.At the same time,this research is to lay out its system design framework after the improvement of the CNN algorithm,and it integrates re⁃lated technologies and algorithms to improve one by one.
作者
曾劲松
ZENG Jinsong(Southwestern University of Finance and Economics,Chengdu 610000)
出处
《计算机与数字工程》
2021年第12期2606-2610,共5页
Computer & Digital Engineering
基金
国家自然科学基金委员会联合基金项目(编号:U19A2078)资助。
关键词
CNN算法
文本情感
人工智能
系统设计
CNN algorithm
text emotion
artificial intelligence
system design
