Hybrid-patent classification based on patent-network analysis
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Cited by:
- Ma, Tingting & Zhang, Yi & Huang, Lu & Shang, Lining & Wang, Kangrui & Yu, Huizhu & Zhu, Donghua, 2017. "Text mining to gain technical intelligence for acquired target selection: A case study for China's computer numerical control machine tools industry," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 162-180.
- Adam B. Jaffe & Gaétan de Rassenfosse, 2017.
"Patent citation data in social science research: Overview and best practices,"
Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(6), pages 1360-1374, June.
- Adam B. Jaffe & Gaétan de Rassenfosse, 2016. "Patent Citation Data in Social Science Research: Overview and Best Practices," NBER Working Papers 21868, National Bureau of Economic Research, Inc.
- Kamal Sanguri & Atanu Bhuyan & Sabyasachi Patra, 2020. "A semantic similarity adjusted document co-citation analysis: a case of tourism supply chain," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 233-269, October.
- Choi, Seokkyu & Lee, Hyeonju & Park, Eunjeong & Choi, Sungchul, 2022. "Deep learning for patent landscaping using transformer and graph embedding," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
- Yu-Shan Chen & Chun-Yu Shih & Ching-Hsun Chang, 2014. "Explore the new relationship between patents and market value: a panel smooth transition regression (PSTR) approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1145-1159, February.
- Lorenz Brachtendorf & Fabian Gaessler & Dietmar Harhoff, 2023. "Truly standard‐essential patents? A semantics‐based analysis," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 32(1), pages 132-157, January.
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