基于生物医学概念提取的信息检索模型:在MeSH上的应用

Mondher Sendi, Mohamed Nazih Omri
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引用次数: 5

摘要

提出了一种新的生物医学概念提取近似模型。该模型基于可能性网络、统计计算和语义接近。可能性网络用于表示MeSH结构,以便为生物医学文本选择相关概念。此外,我们提出了一种通过识别概念之间的语义关系来丰富MeSH词库的模型。提取模型的结果用于在信息检索过程中映射查询。并且,为了证明我们的模型在信息检索上下文中的意义,我们使用了向量模型和OHSUMED集合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biomedical concept extraction based Information Retrieval model: application on the MeSH
This paper proposes a new approximate model for biomedical concept extraction. This model is based on possibilistic network, statistical computing and semantic proximity. The possibilistic network is used for representing the MeSH structure in order to select the relevant concepts for a biomedical text. Moreover, we propose an enrichment model of the MeSH thesaurus by the identification of the semantic relations between concepts. The results of the extraction model serve to mapping a query in an information retrieval process. And, to prove the significance of our model in the Information Retrieval context, we used a vector model and the OHSUMED collection.
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