• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

医学文献数据库(MEDLINE)中的检索反馈

Retrieval feedback in MEDLINE.

作者信息

Srinivasan P

机构信息

Department of Computer Science, Cornell University, Ithaca, NY, USA.

出版信息

J Am Med Inform Assoc. 1996 Mar-Apr;3(2):157-67. doi: 10.1136/jamia.1996.96236284.

DOI:10.1136/jamia.1996.96236284
PMID:8653452
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC116298/
Abstract

OBJECTIVE

To investigate a new approach for query expansion based on retrieval feedback. The first objective in this study was to examine alternative query-expansion methods within the same retrieval-feedback framework. The three alternatives proposed are: expansion on the MeSH query field alone, expansion on the free-text field alone, and expansion on both the MeSH and the free-text fields. The second objective was to gain further understanding of retrieval feedback by examining possible dependencies on relevant documents during the feedback cycle.

DESIGN

Comparative study of retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a MEDLINE test collection of 75 queries and 2,334 MEDLINE citations.

MEASUREMENTS

Retrieval effectivenesses of the original unexpanded and the alternative expanded queries were compared using 11-point-average precision scores (11-AvgP). These are averages of precision scores obtained at 11 standard recall points.

RESULTS

All three expansion strategies significantly improved the original queries in terms of retrieval effectiveness. Expansion on MeSH alone was equivalent to expansion on both MeSH and the free-text fields. Expansion on the free-text field alone improved the queries significantly less than did the other two strategies. The second part of the study indicated that retrieval-feedback-based expansion yields significant performance improvements independent of the availability of relevant documents for feedback information.

CONCLUSIONS

Retrieval feedback offers a robust procedure for query expansion that is most effective for MEDLINE when applied to the MeSH field.

摘要

目的

研究一种基于检索反馈的查询扩展新方法。本研究的首要目标是在同一检索反馈框架内检验替代查询扩展方法。提出的三种替代方法为:仅在医学主题词(MeSH)查询字段上扩展、仅在自由文本字段上扩展以及在MeSH和自由文本字段上都扩展。第二个目标是通过检查反馈周期中对相关文档的可能依赖性,进一步了解检索反馈。

设计

使用原始未扩展和替代扩展的用户查询,对包含75个查询和2334篇MEDLINE引文的MEDLINE测试集进行检索效果的比较研究。

测量

使用11点平均精度得分(11-AvgP)比较原始未扩展和替代扩展查询的检索效果。这些是在11个标准召回点获得的精度得分的平均值。

结果

所有三种扩展策略在检索效果方面均显著改善了原始查询。仅在MeSH上扩展等同于在MeSH和自由文本字段上都扩展。仅在自由文本字段上扩展对查询的改善明显小于其他两种策略。研究的第二部分表明,基于检索反馈的扩展在性能上有显著提升,且与用于反馈信息的相关文档的可用性无关。

结论

检索反馈为查询扩展提供了一种强大的方法,当应用于MeSH字段时,对MEDLINE最为有效。

相似文献

1
Retrieval feedback in MEDLINE.医学文献数据库(MEDLINE)中的检索反馈
J Am Med Inform Assoc. 1996 Mar-Apr;3(2):157-67. doi: 10.1136/jamia.1996.96236284.
2
On the query reformulation technique for effective MEDLINE document retrieval.针对有效 MEDLINE 文档检索的查询改写技术。
J Biomed Inform. 2010 Oct;43(5):686-93. doi: 10.1016/j.jbi.2010.04.005. Epub 2010 Apr 13.
3
Query expansion using the UMLS Metathesaurus.使用统一医学语言系统元词表进行查询扩展。
Proc AMIA Annu Fall Symp. 1997:485-9.
4
Identification of the Best Semantic Expansion to Query PubMed Through Automatic Performance Assessment of Four Search Strategies on All Medical Subject Heading Descriptors: Comparative Study.通过对所有医学主题词描述符的四种检索策略进行自动性能评估来确定查询PubMed的最佳语义扩展:比较研究
JMIR Med Inform. 2020 Jun 4;8(6):e12799. doi: 10.2196/12799.
5
Retrieval feedback for query design in MEDLINE. A comparison with expert network and LLSF approaches.医学文献数据库(MEDLINE)中查询设计的检索反馈。与专家网络和低级别语义框架(LLSF)方法的比较。
Proc AMIA Annu Fall Symp. 1996:353-7.
6
Evaluation of Query Expansion Using MeSH in PubMed.在PubMed中使用医学主题词表(MeSH)进行查询扩展的评估
Inf Retr Boston. 2009;12(1):69-80. doi: 10.1007/s10791-008-9074-8.
7
Study of query expansion techniques and their application in the biomedical information retrieval.查询扩展技术及其在生物医学信息检索中的应用研究。
ScientificWorldJournal. 2014 Mar 2;2014:132158. doi: 10.1155/2014/132158. eCollection 2014.
8
Assessing thesaurus-based query expansion using the UMLS Metathesaurus.使用统一医学语言系统(UMLS)元词表评估基于词库的查询扩展。
Proc AMIA Symp. 2000:344-8.
9
Evaluating relevance ranking strategies for MEDLINE retrieval.评估用于MEDLINE检索的相关性排序策略。
J Am Med Inform Assoc. 2009 Jan-Feb;16(1):32-6. doi: 10.1197/jamia.M2935. Epub 2008 Oct 24.
10
Improving image retrieval effectiveness via query expansion using MeSH hierarchical structure.利用 MeSH 层次结构进行查询扩展以提高图像检索效果。
J Am Med Inform Assoc. 2013 Nov-Dec;20(6):1014-20. doi: 10.1136/amiajnl-2012-000943. Epub 2012 Sep 5.

引用本文的文献

1
Synonym, topic model and predicate-based query expansion for retrieving clinical documents.用于检索临床文档的同义词、主题模型和基于谓词的查询扩展
AMIA Annu Symp Proc. 2012;2012:1050-9. Epub 2012 Nov 3.
2
Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval.医学文献数据库检索中用于伪相关反馈的术语排序算法评估
Healthc Inform Res. 2011 Jun;17(2):120-30. doi: 10.4258/hir.2011.17.2.120. Epub 2011 Jun 30.
3
An overview of MetaMap: historical perspective and recent advances.MetaMap 概述:历史视角与最新进展。
J Am Med Inform Assoc. 2010 May-Jun;17(3):229-36. doi: 10.1136/jamia.2009.002733.
4
MeSH Up: effective MeSH text classification for improved document retrieval.医学主题词表升级:用于改进文档检索的有效医学主题词表文本分类。
Bioinformatics. 2009 Jun 1;25(11):1412-8. doi: 10.1093/bioinformatics/btp249. Epub 2009 Apr 17.
5
Automatic summarization of MEDLINE citations for evidence-based medical treatment: a topic-oriented evaluation.基于证据的医学治疗的 MEDLINE 引文自动摘要:面向主题的评估。
J Biomed Inform. 2009 Oct;42(5):801-13. doi: 10.1016/j.jbi.2008.10.002. Epub 2008 Nov 5.
6
Semantic processing to support clinical guideline development.支持临床指南制定的语义处理
AMIA Annu Symp Proc. 2008 Nov 6;2008:187-91.
7
Biomedical ontologies in action: role in knowledge management, data integration and decision support.生物医学本体的应用:在知识管理、数据集成和决策支持中的作用。
Yearb Med Inform. 2008:67-79.
8
Knowledge-based methods to help clinicians find answers in MEDLINE.基于知识的方法,帮助临床医生在医学文献数据库(MEDLINE)中查找答案。
J Am Med Inform Assoc. 2007 Nov-Dec;14(6):772-80. doi: 10.1197/jamia.M2407. Epub 2007 Aug 21.
9
Essie: a concept-based search engine for structured biomedical text.Essie:一个用于结构化生物医学文本的基于概念的搜索引擎。
J Am Med Inform Assoc. 2007 May-Jun;14(3):253-63. doi: 10.1197/jamia.M2233. Epub 2007 Feb 28.
10
A tutorial on information retrieval: basic terms and concepts.信息检索教程:基本术语和概念
J Biomed Discov Collab. 2006 Mar 13;1:2. doi: 10.1186/1747-5333-1-2.

本文引用的文献

1
Words or concepts: the features of indexing units and their optimal use in information retrieval.词汇或概念:索引单元的特征及其在信息检索中的最佳应用。
Proc Annu Symp Comput Appl Med Care. 1993:685-9.
2
Ambiguity resolution while mapping free text to the UMLS Metathesaurus.将自由文本映射到UMLS元词表时的歧义消解
Proc Annu Symp Comput Appl Med Care. 1994:240-4.
3
A performance and failure analysis of SAPHIRE with a MEDLINE test collection.使用MEDLINE测试集对SAPHIRE进行性能与故障分析。
J Am Med Inform Assoc. 1994 Jan-Feb;1(1):51-60. doi: 10.1136/jamia.1994.95236136.