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Semantic similarities between a keyword database and a controlled vocabulary database: An investigation in the antibiotic resistance literature

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  • Jian Qin

Abstract

The KeyWords Plus in the Science Citation Index database represents an approach to combining citation and semantic indexing in describing the document content. This paper explores the similarities or dissimilarities between citation‐semantic and analytic indexing. The dataset consisted of over 400 matching records in the SCI and MEDLINE databases on antibiotic resistance in pneumonia. The degree of similarity in indexing terms was found to vary on a scale from completely different to completely identical with various levels in between. The within‐document similarity in the two databases was measured by a variation on the Jaccard Coefficient—the Inclusion Index. The average inclusion coefficient was 0.4134 for SCI and 0.3371 for MEDLINE. The 20 terms occurring most frequently in each database were identified. The two groups of terms shared the same terms that consist of the “intellectual base” for the subject. Conceptual similarity was analyzed through scatterplots of matching and nonmatching terms vs. partially identical and broader/narrower terms. The study also found that both databases differed in assigning terms in various semantic categories. Implications of this research and further studies are suggested.

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  • Jian Qin, 2000. "Semantic similarities between a keyword database and a controlled vocabulary database: An investigation in the antibiotic resistance literature," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 51(2), pages 166-180.
    • Handle: RePEc:bla:jamest:v:51:y:2000:i:2:p:166-180
    DOI: 10.1002/(SICI)1097-4571(2000)51:23.0.CO;2-Z
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    Cited by:

    1. Xianwen Wang & Zhi Wang & Shenmeng Xu, 2013. "Tracing scientist’s research trends realtimely," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 717-729, May.
    2. Frid-Nielsen, Snorre Sylvester & Rubin, Olivier & Baekkeskov, Erik, 2019. "The state of social science research on antimicrobial resistance," Social Science & Medicine, Elsevier, vol. 242(C).
    3. Strotmann, Andreas & Zhao, Dangzhi, 2010. "Combining commercial citation indexes and open-access bibliographic databases to delimit highly interdisciplinary research fields for citation analysis," Journal of Informetrics, Elsevier, vol. 4(2), pages 194-200.
    4. Martin G. Moehrle & Jan M. Gerken, 2012. "Measuring textual patent similarity on the basis of combined concepts: design decisions and their consequences," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 805-826, June.
    5. Rey-Long Liu, 2017. "A new bibliographic coupling measure with descriptive capability," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 915-935, February.
    6. Tian, Yangge & Wen, Cheng & Hong, Song, 2008. "Global scientific production on GIS research by bibliometric analysis from 1997 to 2006," Journal of Informetrics, Elsevier, vol. 2(1), pages 65-74.
    7. Martin G. Moehrle, 2010. "Measures for textual patent similarities: a guided way to select appropriate approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 95-109, October.
    8. Christian Sternitzke & Isumo Bergmann, 2009. "Similarity measures for document mapping: A comparative study on the level of an individual scientist," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(1), pages 113-130, January.
    9. Ling-Li Li & Guohua Ding & Nan Feng & Ming-Huang Wang & Yuh-Shan Ho, 2009. "Global stem cell research trend: Bibliometric analysis as a tool for mapping of trends from 1991 to 2006," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 39-58, July.
    10. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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