数据采集与处理2017，Vol.32Issue(4)：838-843,6.DOI:10.16337/j.1004-9037.2017.04.023
基于最大熵的越南语新闻事件元素抽取方法
Extractiond Method of Vietnamese News Event Elements Based on Maximum Entropy
摘要
Abstract
The study on extraction of Vietnamese news event elements is rare,while Vietnam is a significant neighboring country with political,military and economic cooperation,which is just at a distance of a river with us.According to the Vietnamese characteristics,this paper puts forward a method of Vietnamese news event element extraction based on maximum entropy model.This method selects the context,adjacent trigger words and neighboring entities as features,delimits feature templates,trains Vietnamese news events model and achieves the extraction of news event elements of Vietnamese on the basis of the characteristics of the Vietnamese sentence structure and lexical semantic using the maximum entropy algorithm.The experimental result of the extraction shows that the accuracy of the news event elements extracted by the method proposed in this paper reaches more than 80％.关键词
越南语/最大熵/机器学习/新闻事件元素抽取Key words
Vietnamese/maximum entropy/machine learning/news event elements extraction分类
信息技术与安全科学引用本文复制引用
周枫,庙介璞,潘清清,严馨,余正涛..基于最大熵的越南语新闻事件元素抽取方法[J].数据采集与处理,2017,32(4):838-843,6.基金项目
国家自然科学基金(61462055,61562049)资助项目. （61462055,61562049）
