摘要
在利用传统挖掘方法对网络舆情大数据传播特征进行挖掘时,存在挖掘结果与实际情况不符的问题。基于此,笔者重点探讨人工智能技术在网络舆情大数据传播特征挖掘中的应用,首先分析了网络舆情大数据的概念和网络舆情大数据的传播特点,进而分析了网络舆情大数据的传播特征,最后利用人工智能技术对大数据传播特征分类进行分析。实验结果表明,与传统挖掘方法相比,设计的挖掘方法与实际更相符,精度更高。
When using traditional mining methods to mine the dissemination characteristics of online public opinion big data,there is a problem that the mining results do not match the actual situation.Based on this,the author focuses on the application of artificial intelligence technology in the mining of the dissemination characteristics of online public opinion big data.First,it analyzes the concept of online public opinion big data and the dissemination characteristics of online public opinion big data,and then analyzes the dissemination characteristics of online public opinion big data.Finally,artificial intelligence technology is used to analyze the classification of big data dissemination characteristics.The experimental results show that,compared with the traditional mining method,the designed mining method is more consistent with the actual situation and has higher accuracy.
作者
曹剑侠
CAO Jianxia(School of Information Engineering,Zhengzhou University of Industrial Technology,Zhengzhou Henan 451150,China)
出处
《信息与电脑》
2021年第8期168-170,共3页
Information & Computer
关键词
网络舆情大数据
传播特征
数据挖掘
人工智能技术
Internet public opinion big data
communication characteristics
data mining
artificial intelligence technology
