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Power source roadmaps using bibliometrics and database tomography

Author

Listed:
  • Kostoff, R.N.
  • Tshiteya, R.
  • Pfeil, K.M.
  • Humenik, J.A.
  • Karypis, G.

Abstract

Database Tomography (DT) is a textual database analysis system consisting of two major components: (1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical closeness of the multi-word technical phrases) from any type of large textual database, to augment (2) interpretative capabilities of the expert human analyst. DT was used to derive technical intelligence from a Power Sources database derived from the Science Citation Index. Phrase frequency analysis by the technical domain experts provided the pervasive technical themes of the Power Sources database, and the phrase proximity analysis provided the relationships among the pervasive technical themes. Bibliometric analysis of the Power Sources literature supplemented the DT results with author/journal/institution/country publication and citation data.

Suggested Citation

  • Kostoff, R.N. & Tshiteya, R. & Pfeil, K.M. & Humenik, J.A. & Karypis, G., 2005. "Power source roadmaps using bibliometrics and database tomography," Energy, Elsevier, vol. 30(5), pages 709-730.
    • Handle: RePEc:eee:energy:v:30:y:2005:i:5:p:709-730
    DOI: 10.1016/j.energy.2004.04.058
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    References listed on IDEAS

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    1. Ronald N. Kostoff & J. Antonio del Río & James A. Humenik & Esther Ofilia García & Ana María Ramírez, 2001. "Citation mining: Integrating text mining and bibliometrics for research user profiling," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 52(13), pages 1148-1156.
    2. R. N. Kostoff & Henry J. Eberhart & Darrell Ray Toothman, 1999. "Hypersonic and supersonic flow roadmaps using bibliometrics and database tomography," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(5), pages 427-447.
    3. Michael D. Gordon & Susan Dumais, 1998. "Using latent semantic indexing for literature based discovery," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(8), pages 674-685.
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    1. Kiriyama, Eriko & Kajikawa, Yuya & Fujita, Katsuhide & Iwata, Shuichi, 2013. "A lead for transvaluation of global nuclear energy research and funded projects in Japan," Applied Energy, Elsevier, vol. 109(C), pages 145-153.
    2. Rizzi, Francesco & van Eck, Nees Jan & Frey, Marco, 2014. "The production of scientific knowledge on renewable energies: Worldwide trends, dynamics and challenges and implications for management," Renewable Energy, Elsevier, vol. 62(C), pages 657-671.
    3. Hsin-Ning Su & Pei-Chun Lee, 2010. "Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 65-79, October.
    4. Kiriyama, Eriko & Kajikawa, Yuya, 2014. "A multilayered analysis of energy security research and the energy supply process," Applied Energy, Elsevier, vol. 123(C), pages 415-423.
    5. Ogawa, Takaya & Kajikawa, Yuya, 2017. "Generating novel research ideas using computational intelligence: A case study involving fuel cells and ammonia synthesis," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 41-47.
    6. Su, Hsin-Ning & Lee, Pei-Chun, 2012. "Framing the structure of global open innovation research," Journal of Informetrics, Elsevier, vol. 6(2), pages 202-216.
    7. Ogawa, Takaya & Kajikawa, Yuya, 2015. "Assessing the industrial opportunity of academic research with patent relatedness: A case study on polymer electrolyte fuel cells," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 469-475.
    8. Martin, Hilary & Daim, Tugrul U., 2012. "Technology roadmap development process (TRDP) for the service sector: A conceptual framework," Technology in Society, Elsevier, vol. 34(1), pages 94-105.

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