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Forecasting emerging technologies: A supervised learning approach through patent analysis

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  1. Lijie Feng & Kehui Liu & Jinfeng Wang & Kuo-Yi Lin & Ke Zhang & Luyao Zhang, 2022. "Identifying Promising Technologies of Electric Vehicles from the Perspective of Market and Technical Attributes," Energies, MDPI, vol. 15(20), pages 1-22, October.
  2. Lu, Kun & Yang, Guancan & Wang, Xue, 2022. "Topics emerged in the biomedical field and their characteristics," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  3. François Lafond & Daniel Kim, 2019. "Long-run dynamics of the U.S. patent classification system," Journal of Evolutionary Economics, Springer, vol. 29(2), pages 631-664, April.
  4. Serkan Altuntas & Zulfiye Erdogan & Turkay Dereli, 2020. "A clustering-based approach for the evaluation of candidate emerging technologies," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1157-1177, August.
  5. Ziwei Fa & Xinchun Li & Quanlong Liu & Zunxiang Qiu & Zhengyuan Zhai, 2021. "Correlation in Causality: A Progressive Study of Hierarchical Relations within Human and Organizational Factors in Coal Mine Accidents," IJERPH, MDPI, vol. 18(9), pages 1-16, May.
  6. Yuan Zhou & Fang Dong & Yufei Liu & Liang Ran, 2021. "A deep learning framework to early identify emerging technologies in large-scale outlier patents: an empirical study of CNC machine tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 969-994, February.
  7. Ante, Lennart, 2022. "The relationship between readability and scientific impact: Evidence from emerging technology discourses," Journal of Informetrics, Elsevier, vol. 16(1).
  8. Choi, Jaewoong & Yoon, Janghyeok, 2022. "Measuring knowledge exploration distance at the patent level: Application of network embedding and citation analysis," Journal of Informetrics, Elsevier, vol. 16(2).
  9. Wang, Zhinan & Porter, Alan L. & Wang, Xuefeng & Carley, Stephen, 2019. "An approach to identify emergent topics of technological convergence: A case study for 3D printing," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 723-732.
  10. Worasak Klongthong & Veera Muangsin & Chupun Gowanit & Nongnuj Muangsin, 2021. "A Patent Analysis to Identify Emergent Topics and Convergence Fields: A Case Study of Chitosan," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
  11. Uijun Kwon & Youngjung Geum, 2020. "Identification of promising inventions considering the quality of knowledge accumulation: a machine learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1877-1897, December.
  12. Chen, Fan & Wang, Delu & Li, Chunxiao & Mao, Jinqi & Wang, Yadong & Yu, Lan, 2025. "Evolution analysis and trend forecasting for low-carbon technologies in coal power based on a three-layer text mining framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 217(C).
  13. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  14. Youngjae Choi & Sanghyun Park & Sungjoo Lee, 2021. "Identifying emerging technologies to envision a future innovation ecosystem: A machine learning approach to patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5431-5476, July.
  15. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
  16. Higashide, Noriyuki & Zhang, Yi & Asatani, Kimitaka & Miura, Takahiro & Sakata, Ichiro, 2024. "Quantifying advances from basic research to applied research in material science," Technovation, Elsevier, vol. 135(C).
  17. Xiaoxiao Shi & Qingpu Zhang, 2020. "Network inertia and inbound open innovation: is there a bidirectional relationship?," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 791-815, February.
  18. Daiho Uhm & Jea-Bok Ryu & Sunghae Jun, 2017. "An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting," Sustainability, MDPI, vol. 9(11), pages 1-19, November.
  19. Choi, Jaewoong & Lee, Changyong & Yoon, Janghyeok, 2023. "Exploring a technology ecology for technology opportunity discovery: A link prediction approach using heterogeneous knowledge graphs," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
  20. Yang, Zaoli & Zhang, Weijian & Yuan, Fei & Islam, Nazrul, 2021. "Measuring topic network centrality for identifying technology and technological development in online communities," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
  21. Wooseok Jang & Yongtae Park & Hyeonju Seol, 2021. "Identifying emerging technologies using expert opinions on the future: A topic modeling and fuzzy clustering approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6505-6532, August.
  22. Gui, Liang & Wu, Jie & Liu, Peng & Ma, Tieju, 2025. "Recognition of promising technologies considering inventor and assignee's historic performance: A machine learning approach," Technological Forecasting and Social Change, Elsevier, vol. 214(C).
  23. Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
  24. Fa, Ziwei & Li, Xinchun & Qiu, Zunxiang & Liu, Quanlong & Zhai, Zhengyuan, 2021. "From correlation to causality: Path analysis of accident-causing factors in coal mines from the perspective of human, machinery, environment and management," Resources Policy, Elsevier, vol. 73(C).
  25. Sergio Cuellar & Alberto Méndez-Morales & Milton M. Herrera, 2022. "Location Matters: a Novel Methodology for Patent’s National Phase Process," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(3), pages 2138-2163, September.
  26. Natalia Wagner, 2023. "Inventive Activity for Climate Change Mitigation: An Insight into the Maritime Industry," Energies, MDPI, vol. 16(21), pages 1-23, November.
  27. Nicola Amoroso & Annamaria Demarinis Loiotile & Ester Pantaleo & Giuseppe Conti & Shiva Loccisano & Sabina Tangaro & Alfonso Monaco & Roberto Bellotti, 2025. "An Italian Patent Multi-Label Classification System to Support the Innovation Demand and Supply Matching," Sustainability, MDPI, vol. 17(14), pages 1-27, July.
  28. Ki Hong Kim & Young Jae Han & Sugil Lee & Sung Won Cho & Chulung Lee, 2019. "Text Mining for Patent Analysis to Forecast Emerging Technologies in Wireless Power Transfer," Sustainability, MDPI, vol. 11(22), pages 1-24, November.
  29. Yuan Zhou & Fang Dong & Yufei Liu & Zhaofu Li & JunFei Du & Li Zhang, 2020. "Forecasting emerging technologies using data augmentation and deep learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 1-29, April.
  30. Xi, Xi & Ren, Feifei & Yu, Lean & Yang, Jing, 2023. "Detecting the technology's evolutionary pathway using HiDS-trait-driven tech mining strategy," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
  31. Yunlei Lin & Yuan Zhou, 2023. "Identification of Hydrogen-Energy-Related Emerging Technologies Based on Text Mining," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
  32. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
  33. Chung, Park & Sohn, So Young, 2020. "Early detection of valuable patents using a deep learning model: Case of semiconductor industry," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
  34. Huang, Ying & Porter, Alan L. & Zhang, Yi & Lian, Xiangpeng & Guo, Ying, 2019. "An assessment of technology forecasting: Revisiting earlier analyses on dye-sensitized solar cells (DSSCs)," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 831-843.
  35. Choi, Jaewoong & Jeong, Byeongki & Yoon, Janghyeok, 2019. "Technology opportunity discovery under the dynamic change of focus technology fields: Application of sequential pattern mining to patent classifications," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
  36. Puccetti, Giovanni & Giordano, Vito & Spada, Irene & Chiarello, Filippo & Fantoni, Gualtiero, 2023. "Technology identification from patent texts: A novel named entity recognition method," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
  37. Xu, Shuo & Hao, Liyuan & Yang, Guancan & Lu, Kun & An, Xin, 2021. "A topic models based framework for detecting and forecasting emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
  38. Zhang, Hao & Daim, Tugrul & Zhang, Yunqiu (Peggy), 2021. "Integrating patent analysis into technology roadmapping: A latent dirichlet allocation based technology assessment and roadmapping in the field of Blockchain," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
  39. Zhu, Lin & Cunningham, Scott W., 2022. "Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  40. Junseok Lee & Ji-Ho Kang & Sunghae Jun & Hyunwoong Lim & Dongsik Jang & Sangsung Park, 2018. "Ensemble Modeling for Sustainable Technology Transfer," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
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