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基于语义Web的智能信息检索模型

Intelligent information retrieval model based on semantic Web
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摘要 针对传统基于关键字的信息检索系统查全率和查准率都不高的缺点,提出了一种基于语义Web的智能信息检索模型,此模型在语义Web的环境下,利用本体技术,将最初的检索词通过查询扩展模块得到更完善的检索词集,然后利用扩展的检索词集进行检索。将基于关键字匹配的信息检索系统提升为基于本体知识库扩展查询的智能检索系统,从而提高了查全率与查准率,满足了人们对信息检索系统的要求。最后给出了模型的一种实施方案。 In this paper,an intelligent information retrieval model based on semantic Web is proposed to solve the low recall and low precision of the traditional keyword-retrieval-based.In semantic Web,the initial index word is applied into the querying extension module via implementing the ontology technology,so that the word's extension can participate in further retrieval processes.As a result,the keyword matching methods in traditional information retrieval systems will be replaced by ontology knowledge-based solutions for carrying out user demands high recall and high precision information retrieval applications.This paper ends with an implementation of this semantic-web-based model.
出处 《河北省科学院学报》 CAS 2013年第2期22-25,44,共5页 Journal of The Hebei Academy of Sciences
关键词 信息检索 本体 LUCENE 查询扩展 Information retrieval Ontology Lucene Query expansion
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