摘要
当今互联网中的热点话题直接反映了师生的舆情动态,成为学校管理和监督的一个重要环节。因此,话题跟踪研究受到更多的关注,诞生了话题跟踪技术。该技术的提出是为了对海量的互联网资源中未知话题的识别和对已知话题的持续性跟踪。但是,网络数据量的增长速度快,传统的话题跟踪研究面对大规模数据时出现了技术上的瓶颈。为了更好提高话题跟踪检测的效率和准确率,本文将大数据的处理技术引入到话题跟踪研究中,通过对师生访问微博数据的采集,针对采集的数据实现话题跟踪研究,及时把握舆情动态,实现突发事件的预警。
Hot topics on the Internet today directly reflect the public opinions of teachers and students,and become an important part of school management and supervision.Therefore,opic tracking research has attracted more attention,and topic tracking technology has been born.This technology is proposed for the identification of unknown topics in the vast Internet resources and the continuous tracking of known topics.However,with the rapid growth of network data volume,the traditional topic tracking research faces a technical bottleneck in the face of large-scale data.In order to better improve the efficiency and accuracy of topic tracking detection,this paper introduces the processing technology of big data into topic tracking research.By collecting the data of teachers and students’visits to weibo,the collected data can be used to realize topic tracking research,timely grasp the public opinion dynamics,and realize the early warning of emergencies.
作者
骆梅柳
LUO Meiliu(Department of information,Jiangsu College of Finance&Accouting,Lianyungang,222062,Jiangsu,China)
出处
《智能计算机与应用》
2020年第8期287-289,共3页
Intelligent Computer and Applications
基金
2018年江苏省高校哲学社会科学研究基金(2018SJA2019)
关键词
语义网络
权重计算
话题跟踪
Semantic network
Weight calculation
Topic tracking