摘要
随着网络信息的日益丰富以及语义网络的出现,语义信息检索技术成为当前研究的热点。本文研究一种基于语义相似度的信息检索方法,利用本体在语义刻画上的优势,以概念相似度和属性相似度作为语义检索的衡量依据,对语义检索过程的分析和结果的统计表明,文档语义特征向量的概念及属性数的增加有利于改善检索效果。
With exponential growth of web information and emergence of semantic web, semantic information retrieval becomes a hotspot of current research. In this paper, a novel information retrieval method based on semantic similarity is studied . By exploiting the advantage of ontology in describing semantic as well as in computing the Concept - Similarity and Property - Similarity for the semantic retrieval algorithm , the proposed method greatly improves the retrieval precision . The statistic analysis of the semantic retrieval experiment results illustrates that the retrieval accuracy is improved significantly with the increase of the feature vector concepts and the properties of the retrieved documents.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2006年第6期696-701,共6页
Pattern Recognition and Artificial Intelligence
基金
国家自然科学基金(No.60573077)
安徽省自然科学基金(No.050420305)资助项目
关键词
本体
语义
信息检索
Ontology, Semantic, Information Retrieval