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Generating novel research ideas using computational intelligence: A case study involving fuel cells and ammonia synthesis

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  • Ogawa, Takaya
  • Kajikawa, Yuya

Abstract

We proposed a method to help researchers create novel research ideas using bibliometrics. Different concepts and techniques exist in different research areas, and when the fields are sufficiently similar, a salient combination of two different areas can lead to the development of novel research. We have assumed that two different research areas, sharing a high number of similar keywords, would be excellent candidates for integration. We combined link mining and text mining techniques to elucidate hidden but implicit opportunities among apparent, explicit research clusters. To demonstrate the effectiveness of our approach, we conducted a case study on fuel cells and ammonia synthesis. Fuel cells are a rapidly growing research field, while ammonia synthesis is relatively mature. Our results successfully extracted a plausible and post-mature research idea.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:tefoso:v:120:y:2017:i:c:p:41-47
    DOI: 10.1016/j.techfore.2017.04.004
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    9. Naoki Shibata & Yuya Kajikawa & Yoshiyuki Takeda & Katsumori Matsushima, 2009. "Comparative study on methods of detecting research fronts using different types of citation," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 571-580, March.
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    Cited by:

    1. Ma, Jing & Abrams, Natalie F. & Porter, Alan L. & Zhu, Donghua & Farrell, Dorothy, 2019. "Identifying translational indicators and technology opportunities for nanomedical research using tech mining: The case of gold nanostructures," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 767-775.
    2. Takaya Ogawa & Mizutomo Takeuchi & Yuya Kajikawa, 2018. "Analysis of Trends and Emerging Technologies in Water Electrolysis Research Based on a Computational Method: A Comparison with Fuel Cell Research," Sustainability, MDPI, vol. 10(2), pages 1-24, February.
    3. Hei-Chia Wang & Tzu-Ting Hsu & Yunita Sari, 2019. "Personal research idea recommendation using research trends and a hierarchical topic model," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1385-1406, December.
    4. Piotr Tomasz Makowski & Yuya Kajikawa, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Papers 2103.02395, arXiv.org.
    5. Takaya Ogawa & Mizutomo Takeuchi & Yuya Kajikawa, 2018. "Comprehensive Analysis of Trends and Emerging Technologies in All Types of Fuel Cells Based on a Computational Method," Sustainability, MDPI, vol. 10(2), pages 1-30, February.
    6. Makowski, Piotr Tomasz & Kajikawa, Yuya, 2021. "Automation-driven innovation management? Toward Innovation-Automation-Strategy cycle," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    7. Yuya Kajikawa, 2022. "Reframing evidence in evidence-based policy making and role of bibliometrics: toward transdisciplinary scientometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5571-5585, September.

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