山西大学学报（自然科学版）2024，Vol.47Issue(4)：727-736,10.DOI:10.13451/j.sxu.ns.2023065
融入事件知识的新闻事件对比聚类方法
A Contrastive Clustering Method of News Events Incorporating Event Knowledge
摘要
Abstract
News event clustering aims to mine several event clusters of different topics from massive news texts.At present,event clustering is mostly based on text semantic representation,but ignoring the guiding role of event knowledge.Due to the iterative pro-cess of representation learning and target clustering,it is easy to cause error accumulation.It can only deal with offline tasks,which limits the processing of real-time news data,and to solve the above problems,this paper proposes a contrastive clustering method of news events incorporating event knowledge.On the basis of text representation,this method incorporates event key information to enrich event representation.The cluster label is used as the representation,and contrastive learning is performed at the instance level and the cluster level.The representation and cluster assignment are jointly learned in an end-to-end manner to realize the clustering of data streams.Experimental results show that the proposed method improves by 3%compared with other baseline models.关键词
事件聚类/事件表征/对比学习/深度聚类Key words
event clustering/event representation/contrastive learning/deep clustering分类
信息技术与安全科学引用本文复制引用
梁晨,余正涛,高盛祥,朱恩昌..融入事件知识的新闻事件对比聚类方法[J].山西大学学报（自然科学版）,2024,47(4):727-736,10.基金项目
国家自然科学基金(61972186 （）
61732005 （）
U21B2027) （）
云南高新技术产业发展项目(201606) （201606）
云南省重大科技专项计划(202103AA080015 （）
202002AD080001-5) （）
云南省基础研究计划(202001AS070014) （202001AS070014）
云南省学术和技术带头人后备人才(202105AC160018) （202105AC160018）
