摘要
针对信息的交互与获取正日益突破时间与空间的限制,提出了一种基于语义技术的语义域话题关联检测相关性判定模型,模型是基于文本理解和语义分析的判定方法,其核心思想是根据不同话题生成对应的语义结构体,使系统能够实现自动根据语义信息对话题进行相关性判定,仿真实验结果表明文本的误检率还是漏检率都得到了明显的降低,因此,结果证明基于语义的信息时序检测模型能够有效提高对报道中语义空间中主题相关性检测的能力,对于话题的时序检测后期的研究有积极的意义。
Information interaction and acquisition are now gradually breaking through the limit of time and space,Text detection technology based on semantic domain has become the new research in this field.This paper proposes topic link detection correlation model based on semantic technology, which involves the basic researches of text comprehension and semantic analysis in relevance determination.It is of great importance for subsequent researches in topic temporal detection.The core of this method is to establish the semantic structures for specific topics,by which the relevance determination can be achieved automatically reacting to the semantic information.
作者
郑学伟
Zheng Xuewei(Liaoning Radio and TV University, Shenyang 110034,China Liaoning Vocational and Technical College of Equipment Manufacturing, Shenyang 110161, China)
出处
《电子测量技术》
2016年第10期42-45,共4页
Electronic Measurement Technology
基金
辽宁省教育厅科技资助(L2014579)
辽宁省现代远程教育学会专项规划课题(2014XH-BXFZ-12)
辽宁广播电视大学规划课题(2014XB02-12)资助项目
关键词
信息检测
关联检测
语义结构
时序属性
topic detection
link detection
semantic structure
temporal feature
