In this paper the task of constructing Chinese news event data for media and communication research was explored,technologies such as natural language processing,deep learning,and unsupervised clustering were utilized to construct an open-ended news event extraction framework.The process of constructing the Chinese news event database could be summarized as processing the original news text,performing syntactic analysis and semantic role recognition,extracting triplets from it,then extracting verbs and converting them into vector representations,followed by dimension reduction and clustering combined with manual annotation to form structured data.Finally,an event importance score was proposed to assess the distribution of events in the news.The framework was tested using news data from the People's Daily,validating the practical value of the research.
NETL
NSTL
维普
万方数据
