摘要
话题跟踪是一项面向新闻报道信息流进行已知话题跟踪的信息处理技术,本文在现有的向量空间描述文档的基础上,实现了一个基于话题更新的话题跟踪算法,提出了基于知网的近义动词分析的跟踪算法及基于知网的近义动词分析和话题更新的话题跟踪算法.实验表明话题更新和同义词近义词的消除提高了话题跟踪算法的性能.
Topic tracking, as one of natural language processing technologies, is to track known topic from the information stream of news media. This paper implements an algorithm of topic tracking based on topic renewal through describing the vector space model. In addition, it also presents an algorithm of topic tracking based on synonymic verb analysis of Hownet, and an algorithm of topic tracking which is combined synonymic verb analysis with topic renewal. The experiments show that topic renewal and synonymic verb analysis can improve the performance of the topic tracking system.
出处
《北京交通大学学报》
CAS
CSCD
北大核心
2009年第5期132-136,共5页
JOURNAL OF BEIJING JIAOTONG UNIVERSITY
基金
教育部科学技术研究重点项目资助(108126)
关键词
自然语言处理
话题跟踪
新闻报道
知网
话题更新
natural language processing
topic tracking
news stories
HowNet
topic renewal