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Received:May 03, 2018 Revised:May 24, 2018
Received:May 03, 2018 Revised:May 24, 2018
中文摘要: 为了帮助读者从大量新闻报道信息中迅速地把握其主要内容,本文分析了事件要素对新闻主要内容的影响,结合新闻报道的基本原则和要求,提出了一种基于混合模型的事件要素提取方法.该方法首先对新闻数据中识别的实体进行加权,然后使用依存句法树分析实体在新闻事件中扮演的角色,并对关于要素的指代现象进行消解,最终融合频率及角色关系对实体加权的方法进行改进,有效地提取出新闻事件关联性较为重要的要素.实验结果表明,本文所述方法能够准确地提取出与新闻事件关联性较强的事件要素,提高了读者快速筛选新闻事件要素的效率.
Abstract:In order to help readers quickly grasp the main content of a large amount of news report information, this paper analyzes the impact of event elements on the main news content, and combines the basic principles and requirements of news reports, proposes a method of extracting event elements based on hybrid model. The proposed method first weighs the entities recognized in the news data, and then uses the dependency syntax tree to analyze the role of entities in news events, and dispels the reference phenomenon of elements. Finally, the fusion frequency and role relationship are used to improve the entity weighting method and effectively extract the important elements of news event relevance. The experimental results show that the method described in this study can accurately extract event elements with strong relevance to news events and improve the efficiency of readers' rapid selection of news event elements.
keywords: Chinese name entity recognition POS tagging Conditional Random Fields (CRF) dependency syntax hybrid model
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基金项目:国家自然科学青年基金项目(61503312)
引用文本:
虞金中,杨先凤,陈雁,李娟.基于混合模型的新闻事件要素提取方法.计算机系统应用,2018,27(12):169-174
YU Jin-Zhong,YANG Xian-Feng,CHEN Yan,LI Juan.News Event Element Extraction Method Based on Mixed Model.COMPUTER SYSTEMS APPLICATIONS,2018,27(12):169-174
虞金中,杨先凤,陈雁,李娟.基于混合模型的新闻事件要素提取方法.计算机系统应用,2018,27(12):169-174
YU Jin-Zhong,YANG Xian-Feng,CHEN Yan,LI Juan.News Event Element Extraction Method Based on Mixed Model.COMPUTER SYSTEMS APPLICATIONS,2018,27(12):169-174