一种基于领域的语义搜索引擎模型SSEM

Internet已成为全球最丰富的数据源,数据类型繁杂且动态变化,如何从中快速准确地检索出用户所需要的信息是一个亟待解决的问题.传统的搜索引擎基于语法的方式进行搜索,缺乏语义信息,难以准确地表达用户的查询需求和被检索对象的文档语义,致使查准率和查全率较低且搜索范围有限.本文对现有的语义检索方法进行了研究,分析了其中存在的问题,在此基础上提出了一种基于领域的语义搜索引擎模型,结合语义Web技术,使用领域本体元数据模型对用户的查询进行语义化规范,依据领域本体模式抽取文档中的知识并RDF化,准确地表达了用户的查询语义和作为被查询对象的文档语义,可以大大提高检索的准确性和检索效率,详细地给出了模型的体系结构、基本功能和工作原理.

A Semantic Search Engine Model Basedon Domain

Internet has become the most abundant data source in the world with complicated and dynamically changing data type.How to quickly and accurately get the information required by users is a problem that needs to be solved urgently.Traditional search engine executes search with a grammatical way and lacks semantic information,so it is difficult to accurately express the user query demand and object retrieval document semantic,the precision and recall are lower and the search range is limited.In this paper,the existing semantic retrieval methods are researched and the existing problems are analyzed,a domain-based semantic search engine model based on semantic web technology is put forward.User query semantic is specified by using domain ontology and metadata model,document knowledge is extracted based on domain ontology pattern and transformed for RDF,which can significantly improve the retrieval accuracy and retrieval efficiency with accurate expression of the user query and the document semantic as the object being queried.The architecture,basic functions and working principles of the model are elaborated in detail.