摘要
本文基于python技术,提出了利用朴素贝叶斯算法实现的影评情感分析系统。首先利用Scrapy爬虫框架获取数据集,然后使用pandas库和正则表达式等技术完成数据清洗;对影评文本采用jieba分词后,使用多项式贝叶斯分类器,构造出一个基于朴素贝叶斯的情感分类模型。通过对模型进行训练,并使用豆瓣网站采集的影评数据进行分类预测。实验结果表明,该模型具有良好的分类效果。
Based on Python technology,this paper proposes a film review emotion analysis system using naive Bayesian algorithm.Firstly,the data set is obtained by using the Scrapy crawler framework.Then the data cleaning is completed by using Pandas and regular expression technology.After Jieba word segmentation for the film review text,a sentiment classification model based on Naive Bayes is constructed by using polynomial Bayesian classifier.After training and testing with the film review data collected on Douban website,the experimental results show that the model has a good classification effect.
作者
邓慈云
余国清
DENG Ciyun;YU Guoqing(Hunan College of Information,Changsha 410200,China)
出处
《智能计算机与应用》
2023年第2期210-212,F0003,共4页
Intelligent Computer and Applications
基金
湖南省哲学社会科学成果评审委员会课题(XSP22YBC417)。
