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Topic based classification and pattern identification in patents

Citations

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Cited by:

  1. Suominen, Arho & Toivanen, Hannes & Seppänen, Marko, 2017. "Firms' knowledge profiles: Mapping patent data with unsupervised learning," Technological Forecasting and Social Change, Elsevier, vol. 115(C), pages 131-142.
  2. Savin, Ivan & Ott, Ingrid & Konop, Chris, 2022. "Tracing the evolution of service robotics: Insights from a topic modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  3. Ivan Savin & Kristina Chukavina & Andrey Pushkarev, 2023. "Topic-based classification and identification of global trends for startup companies," Small Business Economics, Springer, vol. 60(2), pages 659-689, February.
  4. 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.
  5. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
  6. Lee, Hyunmin, 2023. "Converging technology to improve firm innovation competencies and business performance: Evidence from smart manufacturing technologies," Technovation, Elsevier, vol. 123(C).
  7. David Popp, 2019. "Environmental policy and innovation: a decade of research," CESifo Working Paper Series 7544, CESifo.
  8. Jeon, Eunji & Yoon, Naeun & Sohn, So Young, 2023. "Exploring new digital therapeutics technologies for psychiatric disorders using BERTopic and PatentSBERTa," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
  9. Yuan Zhou & Heng Lin & Yufei Liu & Wei Ding, 2019. "A novel method to identify emerging technologies using a semi-supervised topic clustering model: a case of 3D printing industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 167-185, July.
  10. Ghlamallah, Ezzedine & Alexakis, Christos & Dowling, Michael & Piepenbrink, Anke, 2021. "The topics of Islamic economics and finance research," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 145-160.
  11. Ba, Zhichao & Meng, Kai & Ma, Yaxue & Xia, Yikun, 2024. "Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
  12. Yuan, Xiaodong & Li, Xiaotao, 2021. "The evolution of the industrial value chain in China's high-speed rail driven by innovation policies: A patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
  13. Bruns, Stephan B. & Kalthaus, Martin, 2020. "Flexibility in the selection of patent counts: Implications for p-hacking and evidence-based policymaking," Research Policy, Elsevier, vol. 49(1).
  14. Gao, Xue & Rai, Varun & Nemet, Gregory F., 2022. "The roles of learning mechanisms in services: Evidence from US residential solar installations," Energy Policy, Elsevier, vol. 167(C).
  15. Zhai, Dongsheng & Zhai, Liang & Li, Mengyang & He, Xijun & Xu, Shuo & Wang, Feifei, 2022. "Patent representation learning with a novel design of patent ontology: Case study on PEM patents," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
  16. 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).
  17. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
  18. Li, Munan & Wang, Wenshu & Zhou, Keyu, 2021. "Exploring the technology emergence related to artificial intelligence: A perspective of coupling analyses," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
  19. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Sorace, Stefano & Iazzolino, Gianpaolo, 2017. "Does innovation-orientation lead to retail industry growth? Empirical evidence from patent analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 88-94.
  20. Shubbak, Mahmood H., 2019. "Advances in solar photovoltaics: Technology review and patent trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
  21. Righi, Riccardo & Samoili, Sofia & López Cobo, Montserrat & Vázquez-Prada Baillet, Miguel & Cardona, Melisande & De Prato, Giuditta, 2020. "The AI techno-economic complex System: Worldwide landscape, thematic subdomains and technological collaborations," Telecommunications Policy, Elsevier, vol. 44(6).
  22. Gao, Xue & Rai, Varun, 2023. "Knowledge acquisition and innovation quality: The moderating role of geographical characteristics of technology," Technovation, Elsevier, vol. 125(C).
  23. 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).
  24. 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).
  25. Samira Ranaei & Arho Suominen & Alan Porter & Stephen Carley, 2020. "Evaluating technological emergence using text analytics: two case technologies and three approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 215-247, January.
  26. Shengxuan Tang & Ming Cai & Yao Xiao, 2024. "A Cross-Citation-Based Model for Technological Advancement Assessment: Methodology and Application," Sustainability, MDPI, vol. 16(1), pages 1-20, January.
  27. Gao, Xue & Rai, Varun, 2019. "Local demand-pull policy and energy innovation: Evidence from the solar photovoltaic market in China," Energy Policy, Elsevier, vol. 128(C), pages 364-376.
  28. 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).
  29. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2018. "Knowledge Push Curve (KPC) in retailing: Evidence from patented innovations analysis affecting retailers' competitiveness," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 150-160.
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