Ontology-based information retrieval and extraction

Chen-Yu Lee, V. Soo
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引用次数: 19

Abstract

Using domain knowledge and semantics to conduct effective information retrieval (IR) is one of the major challenges in IR. In this paper we introduce a framework that can facilitate information retrieval based on a sharable domain ontology. Specifically we conduct semantic annotation on the descriptive metadata of images or articles and convert metadata automatically into machine readable format in terms of semantic Web representation. The retrieval of an image instance or information extraction of an historic question can then be conducted by matching the semantic and structural descriptions of the user query based on those of the annotated descriptive metadata. We show that with aid of domain ontology, an IR system can achieve a better performance than the keyword-based information retrieval systems.
基于本体的信息检索与提取
利用领域知识和语义进行有效的信息检索是信息检索的主要挑战之一。本文介绍了一个基于共享领域本体的信息检索框架。具体来说,我们对图像或文章的描述性元数据进行语义标注,并将元数据自动转换为机器可读的语义Web表示格式。然后,可以根据带注释的描述性元数据匹配用户查询的语义和结构描述,从而检索图像实例或提取历史问题的信息。研究表明,与基于关键词的信息检索系统相比,基于领域本体的信息检索系统可以获得更好的性能。
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