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Clustering methodologies for identifying country core competencies

Ronald N. Kostoff

Office of Naval Research, Arlington, VA 22217 USA, kostofr{at}onr.navy.mil

J. Antonio del Río

Centro de Investigación en Energía, UNAM, Temixco, Mor. México

Héctor D. Cortés

Centro de Investigación en Energía, UNAM, Temixco, Mor. México

Charles Smith

Booz-Allen Hamilton, Bethesda, MD 20852, USA

Andrew Smith

University of Queensland, Queensland, Australia

Caroline Wagner

University of Ámsterdam, Amsterdam, The Netherlands

Loet Leydesdorff

University of Ámsterdam, Amsterdam, The Netherlands

George Karypis

University of Minnesota, Minneapolis, MN 55455, USA

Guido Malpohl

University of Karlsruhe, Postfach 6980, 76128 Karlsruhe, Germany

Rene Tshiteya

DDL-OMNI Engineering, LLC, 8260 Greensboro Drive, Suite 600, Mclean, VA 22102, USA

The technical structure of the Mexican science and technology literature was determined. A representative database of technical articles was extracted from the Science Citation Index for the year 2002, with each article containing at least one author with a Mexican address. Many different manual and statistical clustering methods were used to identify the structure of the technical literature (especially the science and technology core competencies), and to evaluate the strengths and weaknesses of each technique. Each method is summarized, and its results presented.

Key Words: Mexico • science and technology • bibliometrics • computational linguistics • core competencies • research evaluation • factor analysis • concept clustering • document clustering • data compression • network analysis • Leximancer • CLUTO • greedy string tiling

Journal of Information Science, Vol. 33, No. 1, 21-40 (2007)
DOI: 10.1177/0165551506067124
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H. Kim and Jae Yun Lee
Exploring the emerging intellectual structure of archival studies using text mining: 2001--2004
Journal of Information Science, June 1, 2008; 34(3): 356 - 369.
[Abstract] [PDF]