基于大数据的网络舆情文本挖掘方法  

Text Mining Method of Network Public Opinion Based on Big Data

作　　者：赵宇 ZHAO Yu(Network Management and Maintenance Center,Chengde Public Security Bureau,Chengde Hebei 067000,China)

机构地区：[1]承德市公安局网络管理维护中心,河北承德067000

出　　处：《信息与电脑》2021年第12期184-186,共3页Information & Computer

摘　　要：传统的文本挖掘方法由于不能准确划分网络舆情关键词,导致文本挖掘时的聚类效果不佳。为此,本文提出基于大数据的网络舆情文本挖掘方法。首先,通过分布式处理方法控制系统延展性,创新文本混合数据储存形式,根据建立语义解析机制;其次,划分网络舆情关键词,划分文本特征为定义性原始数据和描述性原始数据;最后,提取网络舆情文本特征,基于大数据构建文本挖掘模型,完成基于大数据的网络舆情文本挖掘方法设计。In the current text mining method,the key words of network public opinion are not clearly divided,which leads to poor clustering effect in text mining.Therefore,this paper studies the Internet public opinion text mining method based on big data.Through the distributed processing method,control system extensibility,innovate the storage form of text mixed data,according to the establishment of semantic analysis mechanism,divide the network public opinion keywords,divide the text features into the definition of original data and descriptive original data,extract the network public opinion text features,and build the text mining model based on big data,Complete the design of network public opinion text mining method based on big data.

关 键 词：大数据分析 网络舆情 文本挖掘 文本特征 聚类效果 语义分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]