Journal article
Quality of Indexing in Online Data Bases
Information processing & management, v 23(3), pp 211-224
01 Jan 1987
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Practical tests by which the quality of subject indexing in online bibliograhic databases can be compared and judged are described. The tests are illustrated with 18 clusters of documents from the medical behavioral science literature and with terms derived from MEDLINE, PsycINFO, BIOSIS, and Excerpta Medica. Every test involves obtaining a cluster of about 5 documents known on some grounds to be associated with subject matter, and retrieving their descriptors from at least 2 databases. Then, the average number of descriptors applied to the documents, the number of descriptors applied to all and to a majority of the documents in the cluster, and the relative rarity of the applied descriptors are tabulated. Comparable statistics emerge on how every database links related documents and discriminates broadly and finely among documents. Qualitative insights are gained into the expressiveness and pertinence of the available indexing terms. For each document cluster, the proposed method obtained a metric for the system functions of indexing.
Metrics
Details
- Title
- Quality of Indexing in Online Data Bases
- Creators
- Howard White - Drexel UniversityBelver Griffith - Drexel University
- Publication Details
- Information processing & management, v 23(3), pp 211-224
- Publisher
- Elsevier Science Ltd
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:A1987H679600005
- Scopus ID
- 2-s2.0-0023247553
- Other Identifier
- 991019173910004721
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- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science