基于描述逻辑的信息检索:在生物医学文献中的应用

Kabil Boukhari, Mohamed Nazih Omri
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引用次数: 5

摘要

文档索引是信息检索中一个相当敏感的阶段。然而,在文件中提出的术语并不足以完全表示它。然后,通过外部资源对隐含信息进行开发,是更好地进行标引的必要条件。为此,提出了一种基于描述逻辑的生物医学文献索引模型,生成相应的索引。文档和外部资源由描述性表达式表示;第一个统计阶段包括为文档中的每个术语分配重要程度和语义部分,以提取MESH主题词表(医学主题词)中最重要的概念。概念提取步骤使用描述逻辑将统计和语义方法结合起来,然后使用清理部分为文档表示选择最重要的索引。在实验阶段,我们使用了OHSUMED集合,这表明了所提出方法的有效性以及在索引过程中使用描述逻辑的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information Retrieval Based on Description Logic: Application to Biomedical Documents
The document indexing is a fairly sensitive phase in the information retrieval. However, terms presented in a document are not sufficient to completely represent it. Then, the exploitation of the implicit information, through external resources, is necessary for better indexing. For this purpose, a new indexing model for biomedical documents based on description logics has been proposed to generate relevant indexes. The documents and the external resource are represented by descriptive expressions; a first statistical phase consists in assigning an importance degree to each term in the document and a semantic part to extract the most important concepts of the MESH thesaurus (Medical Subject Headings). The concept extraction step uses the description logics to combine the statistical and semantic approaches followed by a cleaning part to select the most important indexes for the document representation. For the experiments phase we used the OHSUMED collection, which showed the effectiveness of the proposed approach and the importance of using description logics for the indexing process.
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