The information integration method of semantic web based on agent ontology(SWAO method) was put forward aiming at the problems in current network environment,which integrates,analyzes and processes enormous web information and extracts answers on the basis of semantics. With SWAO method as the clue,the following technologies were studied:the method of concept extraction based on semantic term mining,agent ontology construction method on account of multi-points and the answer extraction in view of semantic inference. Meanwhile,the structural model of the question answering system applying ontology was presented,which adopts OWL language to describe domain knowledge from where QA system infers and extracts answers by Jena inference engine. In the system testing,the precision rate reaches 86%,and the recalling rate is 93%. The experimental results prove that it is feasible to use the method to develop a question answering system,which is valuable for further study in more depth.
构建了一种新型文献检索系统,能够摘要一篇文献中引起读者研究工作关注的那些内容,并返回读者对这些内容的评论,从而帮助用户快速了解该文献的学术价值及不足之处等重要信息。利用文献间的引用关系从其他文献中找到指向一篇文献的评论上下文,借鉴查询-检索模式,将评论转化为一元语言模型所生成的查询,并将原文献划分为句子所构成的文档集,基于KL-divergence检索模型找到原文献中与评论对应的句子。选取得分最高的若干句子构成体现原文献对外影响的摘要。系统基于北京大学研制的智能搜索引擎平台Platform for Applying,Researching And Developing Intelligent Search Engine(PARADISE),具有快速构建可扩展好的优点。
