FULL-TEXT RETRIEVAL OF MEDICAL JOURNAL LITERATURE

医学期刊文献全文检索

• 批准号: 3373862
• 负责人: MARYELLEN C SIEVERT
• 金额: $ 12.43万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-04-01 至 1992-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3373862
• 关键词: abstracting; computer program /software; computer system design /evaluation; indexing; information display; information retrieval; information system analysis; information systems; journals; personal computers

Our current research demonstrates that searching the full-text of medical journals consistently yields a much higher percentage of relevant documents than searching their bibliographic surrogates. It also shows that full-text searches result in a significantly greater number of irrelevant items. A steadily increasing number of full-text biomedical databases, in both online and compact disk format, makes an investigation of better searching techniques for these databases an important area of research in medical information science. We propose to undertake such an investigation. By creating and analyzing careful records of file manipulations on two systems which support large databases of full- text biomedical journals, we shall develop searching techniques for eliminating irrelevant documents without significant loss of those which are relevant. We shall pay particular attention to the process of synonym aggregation, so important for retrieval of relevant documents in full-text files. By analyzing techniques successful on one system but not on the other in terms of system software and file structure, we shall delineate those design features most conducive to successful searching in the full-text databases.

我们目前的研究表明， 医学期刊始终会产生更高比例的 比搜索他们的书目代理人更重要的是相关文件。 它还表明，全文搜索的结果显着 更多不相关的项目。 数量稳步增加 全文生物医学数据库，在线和光盘 格式，研究了更好的搜索技术， 这些数据库是医学研究的重要领域， 信息科学 我们建议进行这样一项 调查 通过创建和分析文件的详细记录， 操作两个系统，支持完整的大型数据库， 文本生物医学期刊，我们将开发搜索技术， 删除不相关的文件，而不会造成重大损失 这是相关的。 我们会特别留意 同义词聚合的过程，对于检索 全文文件中的相关文件。 通过分析技术 在一个系统上成功，但在另一个系统上却不成功。 软件和文件结构，我们将描述这些设计 最有助于在全文中成功检索的功能 数据库。