一个全文知识库的自然语言检索系统的测试。

L M Bernstein, R E Williamson
{"title":"一个全文知识库的自然语言检索系统的测试。","authors":"L M Bernstein, R E Williamson","doi":"10.1002/asi.4630350407","DOIUrl":null,"url":null,"abstract":"“A Navigator of Natural Language Organized Data” (ANNOD) is a retrieval system which combines use of probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for their similarity to natural language queries proposed by users. ANNOD includes common word deletion, word root isolation, query expansion by a thesaurus, and application of a complex empirical matching (ranking) algorithm. The Hepatitis Knowledge Base, the text of a prototype information system, was the file used for testing ANNOD. Responses to a series of users' unrestricted natural language queries were evaluated by three testers. Information needed to answer 85 to 95‰ of the queries was located and displayed in the first few selected paragraphs. It was successful in locating information in both the classified (listed in Table of Contents) and unclassified portions of text. Development of this retrieval system resulted from the complementarity of and interaction between computer science and medical domain expert knowledge. Extension of these techniques to larger knowledge bases is needed to clarify their proper role.","PeriodicalId":79676,"journal":{"name":"Journal of the American Society for Information Science. American Society for Information Science","volume":"35 4","pages":"235-47"},"PeriodicalIF":0.0000,"publicationDate":"1984-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/asi.4630350407","citationCount":"29","resultStr":"{\"title\":\"Testing of a natural language retrieval system for a full text knowledge base.\",\"authors\":\"L M Bernstein, R E Williamson\",\"doi\":\"10.1002/asi.4630350407\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"“A Navigator of Natural Language Organized Data” (ANNOD) is a retrieval system which combines use of probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for their similarity to natural language queries proposed by users. ANNOD includes common word deletion, word root isolation, query expansion by a thesaurus, and application of a complex empirical matching (ranking) algorithm. The Hepatitis Knowledge Base, the text of a prototype information system, was the file used for testing ANNOD. Responses to a series of users' unrestricted natural language queries were evaluated by three testers. Information needed to answer 85 to 95‰ of the queries was located and displayed in the first few selected paragraphs. It was successful in locating information in both the classified (listed in Table of Contents) and unclassified portions of text. Development of this retrieval system resulted from the complementarity of and interaction between computer science and medical domain expert knowledge. Extension of these techniques to larger knowledge bases is needed to clarify their proper role.\",\"PeriodicalId\":79676,\"journal\":{\"name\":\"Journal of the American Society for Information Science. American Society for Information Science\",\"volume\":\"35 4\",\"pages\":\"235-47\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1984-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/asi.4630350407\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Society for Information Science. American Society for Information Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/asi.4630350407\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Society for Information Science. American Society for Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/asi.4630350407","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Testing of a natural language retrieval system for a full text knowledge base.
“A Navigator of Natural Language Organized Data” (ANNOD) is a retrieval system which combines use of probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for their similarity to natural language queries proposed by users. ANNOD includes common word deletion, word root isolation, query expansion by a thesaurus, and application of a complex empirical matching (ranking) algorithm. The Hepatitis Knowledge Base, the text of a prototype information system, was the file used for testing ANNOD. Responses to a series of users' unrestricted natural language queries were evaluated by three testers. Information needed to answer 85 to 95‰ of the queries was located and displayed in the first few selected paragraphs. It was successful in locating information in both the classified (listed in Table of Contents) and unclassified portions of text. Development of this retrieval system resulted from the complementarity of and interaction between computer science and medical domain expert knowledge. Extension of these techniques to larger knowledge bases is needed to clarify their proper role.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automatic Indexing of Documents from Journal Descriptors: A Preliminary Investigation The Persistence of Fraud in the Literature: The Darsee Case An investigation of the optimization of search logic for the MEDLINE database The Medline/full-text research project Computer human interaction for image information systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1