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Discovering new technology opportunities based on patents: Text-mining and F-term analysis

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  • Song, Kisik
  • Kim, Karp Soo
  • Lee, Sungjoo

Abstract

Discovering new technology opportunities has long been a significant issue in both practice and academia. Among various approaches to search for opportunities, one of the most frequently used is to identify emerging or vacant technologies from patent documents. In line with it, this study aims to suggest a novel approach for the development of new technology ideas based on the F-term, which classifies patent documents according to the technical attributes of the inventions described within them. Since the technical attributes are analyzed according to various perspectives through the application of the F-term, which generates detailed and systematic information about technologies, the F-term can provide effective guidelines for generating new technology ideas, if utilized well.

Suggested Citation

  • Song, Kisik & Kim, Karp Soo & Lee, Sungjoo, 2017. "Discovering new technology opportunities based on patents: Text-mining and F-term analysis," Technovation, Elsevier, vol. 60, pages 1-14.
    • Handle: RePEc:eee:techno:v:60-61:y:2017:i::p:1-14
    DOI: 10.1016/j.technovation.2017.03.001
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    References listed on IDEAS

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    1. Yoon, Janghyeok & Park, Hyunseok & Seo, Wonchul & Lee, Jae-Min & Coh, Byoung-youl & Kim, Jonghwa, 2015. "Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 153-167.
    2. Yongho Lee & So Young Kim & Inseok Song & Yongtae Park & Juneseuk Shin, 2014. "Technology opportunity identification customized to the technological capability of SMEs through two-stage patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 227-244, July.
    3. Lee, Changyong & Kang, Bokyoung & Shin, Juneseuk, 2015. "Novelty-focused patent mapping for technology opportunity analysis," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 355-365.
    4. Klevorick, Alvin K. & Levin, Richard C. & Nelson, Richard R. & Winter, Sidney G., 1995. "On the sources and significance of interindustry differences in technological opportunities," Research Policy, Elsevier, vol. 24(2), pages 185-205, March.
    5. Yongtae Park & Sungjoo Lee & Sora Lee, 2012. "Patent analysis for promoting technology transfer in multi-technology industries: the Korean aerospace industry case," The Journal of Technology Transfer, Springer, vol. 37(3), pages 355-374, June.
    6. Kim, Jeeeun & Lee, Sungjoo, 2015. "Patent databases for innovation studies: A comparative analysis of USPTO, EPO, JPO and KIPO," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 332-345.
    7. Lee, Sangjae & Kim, Wanki & Kim, Young Min & Lee, Hyoung Yong & Oh, Kyong Joo, 2014. "The prioritization and verification of IT emerging technologies using an analytic hierarchy process and cluster analysis," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 292-304.
    8. Schellner, Irene, 2002. "Japanese File Index classification and F-terms," World Patent Information, Elsevier, vol. 24(3), pages 197-201, September.
    9. 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.
    10. Nakamura, Hiroko & Suzuki, Shinji & Sakata, Ichiro & Kajikawa, Yuya, 2015. "Knowledge combination modeling: The measurement of knowledge similarity between different technological domains," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 187-201.
    11. Ola Olsson, 2005. "Technological Opportunity and Growth," Journal of Economic Growth, Springer, vol. 10(1), pages 31-53, January.
    12. Caviggioli, Federico, 2016. "Technology fusion: Identification and analysis of the drivers of technology convergence using patent data," Technovation, Elsevier, vol. 55, pages 22-32.
    13. Zhang, Yi & Porter, Alan L. & Hu, Zhengyin & Guo, Ying & Newman, Nils C., 2014. "“Term clumping” for technical intelligence: A case study on dye-sensitized solar cells," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 26-39.
    14. Wang, Ming-Yeu & Fang, Shih-Chieh & Chang, Yu-Hsuan, 2015. "Exploring technological opportunities by mining the gaps between science and technology: Microalgal biofuels," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 182-195.
    15. Astebro, Thomas B. & Dahlin, Kristina B., 2005. "Opportunity knocks," Research Policy, Elsevier, vol. 34(9), pages 1404-1418, November.
    16. Noh, Heeyong & Song, Young-Keun & Lee, Sungjoo, 2016. "Identifying emerging core technologies for the future: Case study of patents published by leading telecommunication organizations," Telecommunications Policy, Elsevier, vol. 40(10), pages 956-970.
    17. Yoon, Byungun & Park, Inchae & Coh, Byoung-youl, 2014. "Exploring technological opportunities by linking technology and products: Application of morphology analysis and text mining," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 287-303.
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