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Prediction of emerging technologies based on analysis of the US patent citation network

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Cited by:

  1. Yang, Chao & Huang, Cui & Su, Jun, 2018. "An improved SAO network-based method for technology trend analysis: A case study of graphene," Journal of Informetrics, Elsevier, vol. 12(1), pages 271-286.
  2. Jeong, Yujin & Park, Inchae & Yoon, Byungun, 2019. "Identifying emerging Research and Business Development (R&BD) areas based on topic modeling and visualization with intellectual property right data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 655-672.
  3. Irina V. Efimenko & Vladimir F. Khoroshevsky, 2017. "Peaks, Slopes, Canyons and Plateaus: Identifying Technology Trends Throughout the Life Cycle," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(02), pages 1-28, April.
  4. Hanlin You & Mengjun Li & Jiang Jiang & Bingfeng Ge & Xueting Zhang, 2017. "Evolution monitoring for innovation sources using patent cluster analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 693-715, May.
  5. 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.
  6. Yi Zhang & Mengjia Wu & Guangquan Zhang & Jie Lu, 2023. "Stepping beyond your comfort zone: Diffusion‐based network analytics for knowledge trajectory recommendation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(7), pages 775-790, July.
  7. Huang, Lu & Chen, Xiang & Ni, Xingxing & Liu, Jiarun & Cao, Xiaoli & Wang, Changtian, 2021. "Tracking the dynamics of co-word networks for emerging topic identification," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
  8. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
  9. Carol Corrado & David Martin & Qianfan Wu, 2020. "Innovation α: What Do IP-Intensive Stock Price Indexes Tell Us about Innovation?," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 31-35, May.
  10. Liu, Zhenfeng & Feng, Jian & Uden, Lorna, 2023. "Technology opportunity analysis using hierarchical semantic networks and dual link prediction," Technovation, Elsevier, vol. 128(C).
  11. Inchae Park & Byungun Yoon, 2018. "Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis," Sustainability, MDPI, vol. 10(11), pages 1-32, November.
  12. Thara Prabhakaran & Hiran H. Lathabai & Susan George, 2019. "Competing, complementary and co-existing paradigms in techno-scientific literature: A case study of Nanotechnology for engineering," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 941-977, March.
  13. Zehra Taşkın, 2021. "Forecasting the future of library and information science and its sub-fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1527-1551, February.
  14. 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).
  15. Chao Yang & Donghua Zhu & Xuefeng Wang & Yi Zhang & Guangquan Zhang & Jie Lu, 2017. "Requirement-oriented core technological components’ identification based on SAO analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1229-1248, September.
  16. 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.
  17. 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.
  18. Huang, Ying & Chen, Lixin & Zhang, Lin, 2020. "Patent citation inflation: The phenomenon, its measurement, and relative indicators to temper its effects," Journal of Informetrics, Elsevier, vol. 14(2).
  19. Jungkyu Park & Eunnyeong Heo & Dongjun Lee, 2017. "Effective R&D investment planning based on technology spillovers: the case of Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 67-82, April.
  20. Lorenzo Napolitano & Evangelos Evangelou & Emanuele Pugliese & Paolo Zeppini & Graham Room, 2017. "Technology networks: the autocatalytic origins of innovation," Papers 1708.03511, arXiv.org, revised Apr 2018.
  21. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
  22. Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
  23. Yuan Wu & Ziwei Li, 2024. "Digital transformation, entrepreneurship, and disruptive innovation: evidence of corporate digitalization in China from 2010 to 2021," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
  24. Ohsung Kwon, 2020. "A study on how startups approach sustainable development through intellectual property," Sustainable Development, John Wiley & Sons, Ltd., vol. 28(4), pages 613-625, July.
  25. Venugopalan, Subhashini & Rai, Varun, 2015. "Topic based classification and pattern identification in patents," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 236-250.
  26. Kim, Dong-hyu & Lee, Heejin & Kwak, Jooyoung, 2017. "Standards as a driving force that influences emerging technological trajectories in the converging world of the Internet and things: An investigation of the M2M/IoT patent network," Research Policy, Elsevier, vol. 46(7), pages 1234-1254.
  27. Zhang, Yi & Wu, Mengjia & Miao, Wen & Huang, Lu & Lu, Jie, 2021. "Bi-layer network analytics: A methodology for characterizing emerging general-purpose technologies," Journal of Informetrics, Elsevier, vol. 15(4).
  28. Qiao Zheng & Lu-Cheng Huang & Fei-Fei Wu & Wu Dan & Zhang Hui, 2017. "Analyzing Technological Knowledge Diffusion Among Technological Fields Using Patent Data: The Example of Microfluidics," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-17, February.
  29. 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.
  30. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
  31. Yoonjung An & Mintak Han & Yongtae Park, 2017. "Identifying dynamic knowledge flow patterns of business method patents with a hidden Markov model," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 783-802, November.
  32. Florian Kreuchauff & Vladimir Korzinov, 2017. "A patent search strategy based on machine learning for the emerging field of service robotics," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 743-772, May.
  33. Tomomi Kito & Nagi Moriya & Junichi Yamanoi, 2020. "Inter-organisational patent opposition network: How companies form adversarial relationships," Papers 2009.04113, arXiv.org.
  34. Jorge Nogueira de Paiva Britto & Leonardo Costa Ribeiro & Eduardo da Motta e Albuquerque, 2019. "Networks of international patent citations: pattern of growth, self-organization and change," Textos para Discussão Cedeplar-UFMG 605, Cedeplar, Universidade Federal de Minas Gerais.
  35. 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.
  36. Tomomi Kito & Nagi Moriya & Junichi Yamanoi, 2021. "Inter-organisational patent opposition network: how companies form adversarial relationships," The Japanese Economic Review, Springer, vol. 72(1), pages 145-166, January.
  37. Moehrle, Martin G. & Caferoglu, Hüseyin, 2019. "Technological speciation as a source for emerging technologies. Using semantic patent analysis for the case of camera technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 776-784.
  38. Appio, Francesco Paolo & Martini, Antonella & Fantoni, Gualtiero, 2017. "The light and shade of knowledge recombination: Insights from a general-purpose technology," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 154-165.
  39. Angelou, K. & Maragakis, M. & Kosmidis, K. & Argyrakis, P., 2021. "The evolution of triangular research and innovation collaborations in the European area," Journal of Informetrics, Elsevier, vol. 15(3).
  40. Xiwen Liu & Xuezhao Wang & Lucheng Lyu & Yanpeng Wang, 2022. "Identifying disruptive technologies by integrating multi-source data," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5325-5351, September.
  41. An, Jaehyeong & Kim, Kyuwoong & Mortara, Letizia & Lee, Sungjoo, 2018. "Deriving technology intelligence from patents: Preposition-based semantic analysis," Journal of Informetrics, Elsevier, vol. 12(1), pages 217-236.
  42. Sung-Seok Ko & Namuk Ko & Doyeon Kim & Hyunseok Park & Janghyeok Yoon, 2014. "Analyzing technology impact networks for R&D planning using patents: combined application of network approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 917-936, October.
  43. Gian Maria Campedelli, 2021. "Where are we? Using Scopus to map the literature at the intersection between artificial intelligence and research on crime," Journal of Computational Social Science, Springer, vol. 4(2), pages 503-530, November.
  44. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
  45. Lu Huang & Xiang Chen & Yi Zhang & Changtian Wang & Xiaoli Cao & Jiarun Liu, 2022. "Identification of topic evolution: network analytics with piecewise linear representation and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5353-5383, September.
  46. Saveria Capellari & Domenico Stefano, 2014. "University-owned and university-invented patents: a network analysis on two Italian universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 313-329, May.
  47. Xipeng Liu & Xinmiao Li, 2022. "Early Identification of Significant Patents Using Heterogeneous Applicant-Citation Networks Based on the Chinese Green Patent Data," Sustainability, MDPI, vol. 14(21), pages 1-27, October.
  48. Xi Yang & Xiang Yu, 2020. "Preventing Patent Risks in Artificial Intelligence Industry for Sustainable Development: A Multi-Level Network Analysis," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
  49. Mirzadeh Phirouzabadi, Amir & Blackmore, Karen & Savage, David & Juniper, James, 2022. "Modelling and simulating a multi-modal and multi-dimensional technology interaction framework: The case of vehicle powertrain technologies in the US market," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
  50. Hanlin You & Mengjun Li & Keith W. Hipel & Jiang Jiang & Bingfeng Ge & Hante Duan, 2017. "Development trend forecasting for coherent light generator technology based on patent citation network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 297-315, April.
  51. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
  52. Andreas Reinstaller & Peter Reschenhofer, 2017. "Using PageRank in the analysis of technological progress through patents: an illustration for biotechnological inventions," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1407-1438, December.
  53. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
  54. Porter, Alan L. & Chiavetta, Denise & Newman, Nils C., 2020. "Measuring tech emergence: A contest," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
  55. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
  56. Ren, Haiying & Zhao, Yuhui, 2021. "Technology opportunity discovery based on constructing, evaluating, and searching knowledge networks," Technovation, Elsevier, vol. 101(C).
  57. Katy Börner & Bruce Edmonds & Staša Milojević & Andrea Scharnhorst, 2017. "Editorial," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 387-390, January.
  58. Shuto Miyashita & Shogo Katoh & Tomohiro Anzai & Shintaro Sengoku, 2020. "Intellectual Property Management in Publicly Funded R&D Program and Projects: Optimizing Principal–Agent Relationship through Transdisciplinary Approach," Sustainability, MDPI, vol. 12(23), pages 1-17, November.
  59. P. G. J. Persoon & R. N. A. Bekkers & F. Alkemade, 2020. "How cumulative is technological knowledge?," Papers 2012.00095, arXiv.org, revised May 2021.
  60. Parraguez, Pedro & Škec, Stanko & e Carmo, Duarte Oliveira & Maier, Anja, 2020. "Quantifying technological change as a combinatorial process," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
  61. Kyebambe, Moses Ntanda & Cheng, Ge & Huang, Yunqing & He, Chunhui & Zhang, Zhenyu, 2017. "Forecasting emerging technologies: A supervised learning approach through patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 125(C), pages 236-244.
  62. Guan, JianCheng & Zuo, KaiRui & Chen, KaiHua & Yam, Richard C.M., 2016. "Does country-level R&D efficiency benefit from the collaboration network structure?," Research Policy, Elsevier, vol. 45(4), pages 770-784.
  63. Jiaojiao Ji & George A. Barnett & Jianxun Chu, 2019. "Global networks of genetically modified crops technology: a patent citation network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 737-762, March.
  64. Chunjuan Luan & Haiyan Hou & Yongtao Wang & Xianwen Wang, 2014. "Are significant inventions more diversified?," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 459-470, August.
  65. Shen, Yung-Chi & Wang, Ming-Yeu & Yang, Ya-Chu, 2020. "Discovering the potential opportunities of scientific advancement and technological innovation: A case study of smart health monitoring technology," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
  66. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
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