Machine-assisted indexing of scientific research summaries
The Smithsonian Science Information Exchange operates a large interdisciplinary information storage and retrieval system covering current and recently concluded research. It annually collects and indexes more than 100,000 summaries of research projects, and then retrieves selected summaries in respo...
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| Published in | Journal of the American Society for Information Science Vol. 26; no. 4; pp. 230 - 236 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Washington, D.C
Wiley Subscription Services, Inc., A Wiley Company
01.07.1975
Wiley Periodicals Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0002-8231 1097-4571 |
| DOI | 10.1002/asi.4630260406 |
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| Summary: | The Smithsonian Science Information Exchange operates a large interdisciplinary information storage and retrieval system covering current and recently concluded research. It annually collects and indexes more than 100,000 summaries of research projects, and then retrieves selected summaries in response to specific requests for information. With the objective of improving its manual subject indexing effort, the Exchange has developed a computer system which indexes word combinations in each summary according to a Classifying Dictionary, prior to review by its professional staff. The combination creates a man‐machine team which is believed to produce more consistent indexing, quicker and at less cost, while maintaining the scientific quality of current indexing practices. The system differs from some other machine approaches by condensing the multitude of text possibilities into restricted and ordered hierarchies. This article discusses the original aims of the system, its operation and the early experience with its implementation. |
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| Bibliography: | istex:41DEE000C85A4B3D144522308FCA418AB703AC1E ark:/67375/WNG-4459T3GD-4 ArticleID:ASI4630260406 SourceType-Scholarly Journals-1 ObjectType-Statistics/Data Report-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0002-8231 1097-4571 |
| DOI: | 10.1002/asi.4630260406 |