摘要
2020年,由于新冠病毒的来袭,能够正确接收有关报道显得格外重要。在众多新闻词条中,可能会错失有关新冠疫情的报道。文章基于朴素贝叶斯算法实现了新闻分类,可以将有关新冠疫情的相关报道识别出来,识别准确率较高,可达95.54%,有一定的使用价值。
In 2020,due to the coming of the COVID-19,it is extremely important to receive relevant reports correctly.Among many news items,reports about the COVID-19 may be missed.This article implements news classification based on the naive Bayes algorithm,which can identify relevant reports about the COVID-19,the recognition accuracy rate can reach 95.54%,and the recognition accuracy rate is high,which has certain use value.
作者
马亚州
张勇
侯益明
王紫薇
Ma Yazhou;Zhang Yong;Hou Yiming;Wang Ziwei(College of Information Science and Engineering,Shanxi Agricultural University,Taigu 030801,China)
出处
《无线互联科技》
2020年第14期120-121,共2页
Wireless Internet Technology
基金
山西农业大学博士科研启动项目,项目名称:农业物联网模型检测技术研究,编号:2017YJ30。
关键词
朴素贝叶斯
分类
识别
Naive Bayes
classification
recognition
