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Development and application of a keyword-based knowledge map for effective R&D planning

Author

Listed:
  • Byungun Yoon

    (Dongguk University-Seoul)

  • Sungjoo Lee

    (Ajou University)

  • Gwanghee Lee

    (National Research Foundation of Korea)

Abstract

With the growing recognition of the importance of knowledge creation, knowledge maps are being regarded as a critical tool for successful knowledge management. However, the various methods of developing knowledge maps mostly depend on unsystematic processes and the judgment of domain experts with a wide range of untapped information. Thus, this research aims to propose a new approach to generate knowledge maps by mining document databases that have hardly been examined, thereby enabling an automatic development process and the extraction of significant implications from the maps. To this end, the accepted research proposal database of the Korea Research Foundation (KRF), which includes a huge knowledge repository of research, is investigated for inducing a keyword-based knowledge map. During the developmental process, text mining plays an important role in extracting meaningful information from documents, and network analysis is applied to visualize the relations between research categories and measure the value of network indices. Five types of knowledge maps (core R&D map, R&D trend map, R&D concentration map, R&D relation map, and R&D cluster map) are developed to explore the main research themes, monitor research trends, discover relations between R&D areas, regions, and universities, and derive clusters of research categories. The results can be used to establish a policy to support promising R&D areas and devise a long-term research plan.

Suggested Citation

  • Byungun Yoon & Sungjoo Lee & Gwanghee Lee, 2010. "Development and application of a keyword-based knowledge map for effective R&D planning," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 803-820, December.
    • Handle: RePEc:spr:scient:v:85:y:2010:i:3:d:10.1007_s11192-010-0294-5
    DOI: 10.1007/s11192-010-0294-5
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    2. María Pinto & Rosaura Fernández-Pascual & David Caballero-Mariscal & Dora Sales, 2020. "Information literacy trends in higher education (2006–2019): visualizing the emerging field of mobile information literacy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1479-1510, August.
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    4. Balaid, Ali & Abd Rozan, Mohd Zaidi & Hikmi, Syed Norris & Memon, Jamshed, 2016. "Knowledge maps: A systematic literature review and directions for future research," International Journal of Information Management, Elsevier, vol. 36(3), pages 451-475.
    5. Hongbing Jiang & Chen Yang & Jian Ma & Thushari Silva & Huaping Chen, 2016. "A social voting approach for scientific domain vocabularies construction," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 803-820, August.
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