COMPARATIVE STUDY OF INDEX TERMS AND FULL-TEXT

越来越多的生物医学期刊 可透过网上搜寻全文，即完整的 每一篇文章的文本被排序，任何文章都可以通过 其中包含的单个单词或单词的组合。 这 代表着信息获取点的急剧增加 在这些日记里。 但是，在某些情况下，全文可用性可能会导致 接入点过多，阻碍了大多数 相关文件。 另一方面，受控指数术语， 代表对重要概念的判断， 文件和判断容易出现人为错误。 本项目旨在检验指标的相对功效 术语和全文检索的文件，在这些 还可进行全文检索的MEDLINE期刊。 将向下列部门索取资料： 内科、外科、家庭和社区医学以及儿童 密苏里-哥伦比亚大学健康科学系 中心 训练有素和经验丰富的搜索人员将搜索 MEDLINE数据库和相应的全文数据库， 相关引文。 将对检索到的所有引文进行评价， 请求者的相关性。 将结果制成表格， 分析以确定哪种检索方法更 在确定相关的书目引用有效，为什么充分- 文本系统遗漏了一些相关文档， 对于某些类型的人来说， 问题. 此外，将分析数据，以确定如何 全文系统中通常相关的项目可能已经被 仅用标题和抽象词来标识。

An increasing number of biomedical journals are being made available for online searching via full-text, that is, the complete text of each article is sorted and any article may be retrieved by a single word or combinations of words contained therein. This represents a dramatic increase in points of access to information in these journals. In some cases, however, full-text availability may present a surfeit of access points and hinder the identification of the most relevant documents. Controlled index terms, on the other hand, represent judgments regarding the important concepts in documents, and judgments are subject to human error. This project is designed to test the relative efficacy of index terms and full-text for the retrieval of documents in those MEDLINE journals for which full-text searching is also available. Information requests will be solicited from the Departments of Medicine, Surgery, Family and Community Medicine, and Child Health at the University of Missouri-Columbia Health Sciences Center. Trained and experienced searchers will search both the MEDLINE database and the corresponding full-text databases for relevant citations. All citations retrieved will be evaluated for relevance by the requesters. Results will be tabulated and analyzed to determine which of the retrieval methods is more effective in identifying relevant bibliographic citations, why full- text systems miss some relevant documents, and whether one method is more effective than the other for certain kinds of questions. In addition, data will be analyzed to determine how often relevant items in full-text systems could have been identified with title and abstract words alone.