摘要
本文主要是对自然语言理解中如何从句子里和段落中提取中心意思进行研究,首先建立合理完善的静态知识库,然后对动词按照相关性进行聚类,最后对聚类的结果按照时间顺序排序。在建立了比较完整的静态知识库的前提下,本文提供的动词事件聚类方法能在中学智能辅导系统领域里对提取文章核心意思具有很高的成功率。
This text mainly studies how to pick up the core meaning from sentences and paragraphs as for natural language understanding. Firstly, the paper builds up a reasonable and perfect static repository, clusters verbs according to their dependency,and finally sorts the clustering results according to the time sequence. On the premise of building an integral static repository, the verb affair clustering method provided in this paper features high rate of success to pick up the core meaning from articles in the intelligence tutoring system for middle schools.
出处
《计算机工程与科学》
CSCD
2008年第3期133-135,141,共4页
Computer Engineering & Science
基金
科技部科技型中小企业创新基金资助项目(01c26226111002)
关键词
领域过程树
本体
静态知识
事件聚类
domain process tree
ontology
static knowledge
affair clustering
