摘要
本文提出一种科技风险事件资源库和事件发现模型的构建方法,通过分析网络新闻源数据的文本特征,利用爬取的科技媒体新闻构建元事件资源库和主题事件再生资源库模型,并提出综合评价模型进行事件发现。针对事件发现,本文提出了一种two-branch Transformer的科技领域风险事件语言模型,从风险事件中提取与风险度相关的词汇特征,并弱化文本自身的领域特征等对风险事件分类任务造成的干扰,以此来发现风险事件。研究结果验证了本文所提出的风险事件发现模型及对元事件风险倾向进行判断的指标的有效性。本文能够为科技领域风险事件资源库的构建提供参考,提出的科技领域风险事件语言模型能够为风险发现研究提供方法和技术上的参考。
This study proposes a method to construct a risk event base and event detection model in the field of science and technology.By analyzing the text features of online news source data,the meta-event resource database and themeevent regenerated resource database models are constructed using crawled news in the field of science and technology,and a comprehensive evaluation model is proposed for event detection.For event detection,this study proposes a two-branch transformer model for risk events,which extracts lexical features related to risk degree from risk events and reduces the interference caused by text domain features to risk event classification,in order to identify risk events.The experimental results show that the proposed risk event detection model and the index for judging the risk propensity of meta-events are effective.This study can provide a reference for risk event base construction in the field of science and technology,and the proposed language model can provide a methodological and technical reference for the study of risk event detection.
作者
刘耀
房小玮
秦迅
Liu Yao;Fang Xiaowei;Qin Xun(Institute of Scientific and Technical Information of China,Beijing 100038;School of Software&Microelectronics,Peking University,Beijing 100091)
出处
《情报学报》
CSSCI
CSCD
北大核心
2022年第11期1188-1198,共11页
Journal of the China Society for Scientific and Technical Information
基金
国家社会科学基金项目“数字资源知识共享与知识再利用模式与方法研究”(21BTQ011)。
关键词
风险事件
元事件抽取
事件发现
事件库
risk event
meta-event extraction
event detection
event base
