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Anticipating technological convergence: Link prediction using Wikipedia hyperlinks

Citations

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Cited by:

  1. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
  2. Hong, Suckwon & Kim, Juram & Woo, Han-Gyun & Kim, Young-Choon & Lee, Changyong, 2022. "Screening ideas in the early stages of technology development: A word2vec and convolutional neural network approach," Technovation, Elsevier, vol. 112(C).
  3. Zhao, Jianyu & Su, Xinjie & Li, Xixi & Xi, Xi & Yao, Xinlin, 2025. "Forecasting technology convergence with the spatiotemporal link prediction model," Technovation, Elsevier, vol. 146(C).
  4. Jungpyo Lee & So Young Sohn, 2021. "Recommendation system for technology convergence opportunities based on self-supervised representation learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 1-25, January.
  5. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
  6. Sasaki, Hajime & Sakata, Ichiro, 2021. "Identifying potential technological spin-offs using hierarchical information in international patent classification," Technovation, Elsevier, vol. 100(C).
  7. Changyong Lee & Suckwon Hong & Juram Kim, 2021. "Anticipating multi-technology convergence: a machine learning approach using patent information," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1867-1896, March.
  8. Chen ZHU & Kazuyuki MOTOHASHI, 2022. "Government R&D spending as a driving force of technology convergence," Discussion papers 22030, Research Institute of Economy, Trade and Industry (RIETI).
  9. Baaden, Philipp & Rennings, Michael & John, Marcus & Bröring, Stefanie, 2024. "On the emergence of interdisciplinary scientific fields: (how) does it relate to science convergence?," Research Policy, Elsevier, vol. 53(6).
  10. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  11. Wang, Jinfeng & Zhang, Zhixin & Feng, Lijie & Lin, Kuo-Yi & Liu, Peng, 2023. "Development of technology opportunity analysis based on technology landscape by extending technology elements with BERT and TRIZ," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
  12. Lee, Changyong & Jeon, Daeseong & Ahn, Joon Mo & Kwon, Ohjin, 2020. "Navigating a product landscape for technology opportunity analysis: A word2vec approach using an integrated patent-product database," Technovation, Elsevier, vol. 96.
  13. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
  14. Zihao Jiang & Jiarong Shi, 2023. "Quantity or quality? Policy effects on innovations in the wind power industry in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(8), pages 4507-4522, December.
  15. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
  16. Mohamed M. Mostafa, 2023. "Twenty years of Wikipedia in scholarly publications: a bibliometric network analysis of the thematic and citation landscape," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(6), pages 5623-5653, December.
  17. Ren, Maohui & Zhou, Tao & Wang, ChenXi, 2024. "New energy vehicle innovation network, innovation resources agglomeration externalities and energy efficiency: Navigating industry chain innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
  18. Wang, Liang & Li, Munan, 2024. "An exploration method for technology forecasting that combines link prediction with graph embedding: A case study on blockchain," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
  19. Zhu, Chen & Motohashi, Kazuyuki, 2022. "Identifying the technology convergence using patent text information: A graph convolutional networks (GCN)-based approach," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
  20. Yang, Guancan & Xing, Jiaxin & Xu, Shuo & Zhao, Yuntian, 2024. "A framework armed with node dynamics for predicting technology convergence," Journal of Informetrics, Elsevier, vol. 18(4).
  21. Seo, Wonchul & Afifuddin, Mokh, 2024. "Developing a supervised learning model for anticipating potential technology convergence between technology topics," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
  22. Jee, Su Jung & Kwon, Minji & Ha, Jung Moon & Sohn, So Young, 2019. "Exploring the forward citation patterns of patents based on the evolution of technology fields," Journal of Informetrics, Elsevier, vol. 13(4).
  23. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
  24. Wang, Chang & Geng, Hongjun & Sun, Rui & Song, Huiling, 2022. "Technological potential analysis and vacant technology forecasting in the graphene field based on the patent data mining," Resources Policy, Elsevier, vol. 77(C).
  25. Changyong Lee & Gyumin Lee, 2019. "Technology opportunity analysis based on recombinant search: patent landscape analysis for idea generation," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 603-632, November.
  26. Chen Zhu & Kazuyuki Motohashi, 2023. "Government R&D spending as a driving force of technology convergence: a case study of the Advanced Sequencing Technology Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 3035-3065, May.
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