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Query specific graph-based query reformulation using UMLS for clinical information access.
Journal of Biomedical informatics ( IF 4.5 ) Pub Date : 2020-06-25 , DOI: 10.1016/j.jbi.2020.103493
Jainisha Sankhavara 1 , Rishi Dave 1 , Bhargav Dave 1 , Prasenjit Majumder 1
Affiliation  

Biomedical document retrieval requires entity level processing instead of term level. This paper explores the usage and impact of UMLS for entity-based query reformulation in biomedical document retrieval. A novel graph-based approach for query reformulation using UMLS is described herein which queries are expanded using biomedical entities. The proposed method considers UMLS entities from a query with their related entities identified by UMLS and constructs a query-specific graph of biomedical entities for term selection. This query reformulation approach is compared with baseline, pseudo relevance feedback based query expansion approach and state-of-the-art UMLS based query reformulation approaches. The experiments on CDS 2015 and CDS 2016 datasets shows 35% and 45% improvement in retrieval performance, respectively.



中文翻译:

使用UMLS进行基于特定图的查询重新查询,以获取临床信息。

生物医学文档检索需要实体级别的处理,而不是术语级别。本文探讨了UMLS在生物医学文档检索中基于实体的查询重新制定的用途和影响。本文描述了一种用于使用UMLS进行查询重构的基于图的新颖方法,该查询使用生物医学实体进行了扩展。所提出的方法从查询中考虑UMLS实体,并通过UMLS标识它们的相关实体,并构建特定于查询的生物医学实体图以进行术语选择。将该查询重构方法与基线,基于伪相关反馈的查询扩展方法和基于最新UMLS的查询重构方法进行了比较。CDS 2015和CDS 2016数据集上的实验分别显示检索性能提高了35%和45%。

更新日期:2020-06-25
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