摘要
为了改善现有突发检测的不足,提出一种融合词特征和Strom框架的突发事件在线检测模型。在基于词特征的检测模型的基础上,使用Strom分布式框架,结合层次聚类算法,在线检测微博事件中的突发事件。实验结果表明进行检索评估测试时取得了较好结果,很好的实现在线检测。
In order to improve the shortcomings of the existing burst detection,an online event detection model combining word fea⁃tures and Strom framework is proposed.On the basis of the word feature-based detection model,the Strom distributed framework is combined with a hierarchical clustering algorithm to detect unexpected events in Weibo events online.The experimental results show that good results are obtained during the retrieval evaluation test,and the online detection is well achieved.
作者
方中纯
宋平
FANG Zhong-chun;Song Ping(Engineering and Training Center,Inner Mongolia University of Science and Technology,Baotou 014010,China;Information Engineering School,Inner Mongolia University of Science and Technology,Baotou 014010,China)
出处
《电脑知识与技术》
2020年第20期211-212,217,共3页
Computer Knowledge and Technology
关键词
突发事件
Strom框架
层次聚类
在线检测
emergencies
storm framework
hierarchical clustering
online detection
