模糊本体在语义信息检索中的应用

Study on application of fuzzy ontology in semantic information retrieval

传统的语义信息检索是基于检索词语义的匹配,无法满足检索不确定的、不完整的信息以及对检索结果进行聚类处理,因此,提出将模糊本体引入语义信息检索方法。该方法以本体技术先建立领域语义模型,各概念的隶属度加到语义建模的过程中,并提供语义标注;以模糊推理方式对概念、公理等本体进一步处理,从而便于计算机计算处理。能够提高在语义信息检索中对模糊信息进行检索的查准率、查全率,采用聚类技术对检索结果进行聚类,以达到智能化检索的目的。

Traditional semantic information retrieval is based on keywords semantic matching and can not meet the retrieval of information and the uncertainty of intelligent search results. This paper summarizes the fuzzy ontology and clustering technology features. It analyzes the feasibility which introduces the fuzzy ontology and the clustering into the semantic information retrieval. Fuzzy ontology can improve the precision and entirety of the semantic information retrieval of uncertainties information retrieval, using clustering technology to cluster the search results in order to achieve the purpose of intelligent retrieval.