Mapping Korea’s national R&D domain of robot technology by using the co-word analysis

In this paper, we show a “Strategic Diagram” of the robot technology by applying the co-word analysis to the metadata of Korean related national R&D projects in 2001. The strategic diagram shows the evolutionary trends of the specific R&D domain and relational patterns between subdomains. We may use this strategic diagram to support both the strategic planning and the R&D Program.

[1]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[2]  Qin He,et al.  Knowledge Discovery Through Co-Word Analysis , 1999, Libr. Trends.

[3]  Thomas E. Potok,et al.  A flocking based algorithm for document clustering analysis , 2006, J. Syst. Archit..

[4]  Loet Leydesdorff,et al.  Co-words and citations relations between document sets and environments , 1988 .

[5]  Katherine W. McCain,et al.  Mapping authors in intellectual space: A technical overview , 1990, J. Am. Soc. Inf. Sci..

[6]  R. Barré,et al.  S&T Indicators for Policy Making in a Changing Science-Society Relationship , 2004 .

[7]  David Knoke,et al.  Social Network Analysis: Methods and Applications. , 1996 .

[8]  Anthony F. J. van Raan,et al.  Monitoring Scientific Developments from a Dynamic Perspective: Self-Organized Structuring to Map Neural Network Research , 1998, Journal of the American Society for Information Science.

[9]  Jean Pierre Courtial,et al.  The use of patent titles for identifying the topics of invention and forecasting trends , 1993, Scientometrics.

[10]  Ed C. M. Noyons,et al.  Monitoring scientific developments from a dynamic perspective: self-organized structuring to map neural network research , 1998 .

[11]  Jean Pierre Courtial,et al.  Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry , 1991, Scientometrics.

[12]  Yuko Fujigaki,et al.  Concept evolution in science and technology policy: The process of change in relationships among university, industry and government , 1998 .

[13]  Loet Leydesdorff,et al.  Top-down decomposition of the Journal Citation Reportof the Social Science Citation Index: Graph- and factor-analytical approaches , 2004, Scientometrics.

[14]  Howard D. White,et al.  Author cocitation: A literature measure of intellectual structure , 1981, J. Am. Soc. Inf. Sci..

[15]  Mykola Galushka,et al.  A scaleable document clustering approach for large document corpora , 2006, Inf. Process. Manag..

[16]  M. Callon,et al.  Mapping the Dynamics of Science and Technology , 1986 .

[17]  Kumiko Miyazaki,et al.  An integrated network approach to systems of innovation--the case of robotics in Japan , 1999 .

[18]  Ronald Rousseau,et al.  Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient , 2003, J. Assoc. Inf. Sci. Technol..

[19]  George Karypis,et al.  Clustering methodologies for identifying country core competencies , 2007, J. Inf. Sci..

[20]  George Karypis,et al.  The structure and infrastructure of Mexico's science and technology , 2005 .

[21]  Loet Leydesdorff,et al.  A validation study of “LEXIMAPPE” , 1992, Scientometrics.

[22]  Mark Huisman,et al.  Software for statistical analysis of social networks , 2004 .

[23]  Yuko Fujigaki Analysis on dynamics of research sub-domains in interdisciplinary fields: Analysis using personal distribution versus papers , 2004, Scientometrics.

[24]  B. Michelet,et al.  Using bibliometrics in strategic analysis: “understanding chemical reactions” at the CNRS , 1991, Scientometrics.

[25]  Henk F. Moed,et al.  Handbook of Quantitative Science and Technology Research , 2005 .

[26]  Gobinda G. Chowdhury,et al.  Bibliometric cartography of information retrieval research by using co-word analysis , 2001, Inf. Process. Manag..