RETRIEVAL FROM FULL-TEXT MEDICAL DATABASES

从全文医学数据库中检索

• 批准号: 2237632
• 负责人: MARYELLEN C SIEVERT
• 金额: $ 17.64万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-09-01 至 1997-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2237632
• 关键词: abstracting; computer system design /evaluation; information retrieval; information system analysis; information systems; vocabulary development for information system

This proposal advocates a continuation of the MEDLINE/Full-Text Research Project which has studied aspects of the retrieval of relevant articles from full-text databases. In carrying out this phase of the project we shall make extensive use of the data which we have accumulated in answering previous research questions. Two of the four new questions to be addressed arise directly from the results of the current quest for heuristics for full-text searching. They are: 1) How many times should a searcher request that a given concept appear in a document--and in which fields--in order to insure optimum retrieval? 2) What effect does the ability to search both the indexing and the natural language of full-text have on retrieval? The third question results from the increasing use of the structured abstract in medical journals; it is, 3) Does the full-text retain its recall advantage now that the structured abstract is available in the bibliographic files? This question arises from the possibility that the structured abstract might be sufficient for retrieval since it covers certain variables which would be of importance in a search. The fourth question has been suggested by physician participants in the project and focusses our search for heuristics on specific types of relevant articles. It is: 4) How can the searcher of full-text manipulate the strategy to retrieve only relevant articles of highest quality? A corollary questions arises: if quality filters are applied to retrieval from full-text databases does the advantage of full-text over MEDLINE remain? The advent of new searching software for full-text in both online systems and CD-ROM products now makes it possible to investigate the first two questions. Data accumulated so far suggests that there is a close relationship between kind of concept being searched and the most effective search heuristic. By repeating a search in both MEDLINE with the structured abstract and in a full-text journal file-we should be able to see if the full-text retains its recall advantage. Finally the obvious need for "quality filters" in medical information retrieval is the impetus for a search for heuristics for the retrieval of the "best" in full-text medical literature.

该提案主张继续进行MEDLINE/全文研究 研究了相关文章检索方面的项目 来自全文数据库。在执行该项目的这一阶段时，我们 将广泛利用我们在#年积累的数据 回答之前的研究问题。四个新问题中的两个是 解决的问题直接源于当前对 用于全文搜索的启发式方法。它们是：1)一个人应该做多少次 搜索者请求将给定的概念出现在文档中--其中 字段--为了确保最佳检索？2) 能够搜索全文的索引和自然语言 有没有取回？第三个问题是由于越来越多地使用 医学期刊中的结构化摘要；它是，3)全文 由于结构化摘要已可用，因此保留了它的检索优势 在书目档案里吗？这个问题产生于这样一种可能性 结构化摘要可能足以进行检索，因为它涵盖 在搜索中具有重要意义的某些变量。第四次 参与该项目的医生提出了一个问题， 将我们的启发式搜索集中在特定类型的相关文章上。 它是：4)全文搜索者如何操纵策略来 只检索最高质量的相关文章？随之而来的问题 出现：如果将质量过滤器应用于从全文检索 数据库全文相对于MEDLINE的优势还在吗？ 在两个在线系统中都出现了新的全文搜索软件 而CD-ROM产品现在使研究前两个成为可能 问题。到目前为止积累的数据表明， 被搜索的概念类型与最有效的概念之间的关系 搜索启发式。通过在两个MEDLINE中使用 结构化摘要和全文日记文件-我们应该能够 看看全文是否保持了它的召回优势。最后，显而易见的是 医学信息检索需要“质量过滤器”是原动力 搜索启发式方法以检索全文中的“Best” 医学文献。