Ontology based semantic information retrieval

J. Mustafa, S. Khan, K. Latif
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引用次数: 17

Abstract

Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries. The main drawback of the existing semantic-based information retrieval techniques is that none of them considers the context of the concept(s). We propose a semantic information retrieval framework to improve the precision of search results. In this paper, thematic similarity approach is employed for information retrieval in order to capture the context of particular concept(s). We store metadata information of source(s) in the form of RDF triples. We search userpsilas queries in the existing metadata by matching RDF triples instead of keywords. The results of the experiments performed on our framework showed improvements in precision and recall compared to the existing semantic-based information retrieval techniques.
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基于本体的语义信息检索
基于语义的信息检索技术理解用户在查询中指定的概念的含义。现有的基于语义的信息检索技术的主要缺点是它们都不考虑概念的上下文。为了提高搜索结果的准确性,我们提出了一个语义信息检索框架。本文采用主题相似度方法进行信息检索,以捕捉特定概念的语境。我们以RDF三元组的形式存储源的元数据信息。我们通过匹配RDF三元组而不是关键字来搜索现有元数据中的用户塞拉斯查询。实验结果表明,与现有的基于语义的信息检索技术相比,我们的框架在准确率和召回率方面有所提高。
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