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“Term clumping” for technical intelligence: A case study on dye-sensitized solar cells

Citations

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Cited by:

  1. Vicente-Gomila, J.M. & Artacho-Ramírez, M.A. & Ting, Ma & Porter, A.L., 2021. "Combining tech mining and semantic TRIZ for technology assessment: Dye-sensitized solar cell as a case," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
  2. 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.
  3. Zhang, Yi & Lu, Jie & Liu, Feng & Liu, Qian & Porter, Alan & Chen, Hongshu & Zhang, Guangquan, 2018. "Does deep learning help topic extraction? A kernel k-means clustering method with word embedding," Journal of Informetrics, Elsevier, vol. 12(4), pages 1099-1117.
  4. Richarz, Jan & Wegewitz, Stephan & Henn, Sarah & Müller, Dirk, 2023. "Graph-based research field analysis by the use of natural language processing: An overview of German energy research," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
  5. Zhang, Lei & Chen, Zhiqiao & Su, Jing & Li, Jingfa, 2019. "Data mining new energy materials from structure databases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 554-567.
  6. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
  7. Huang, Ying & Porter, Alan L. & Cunningham, Scott W. & Robinson, Douglas K.R. & Liu, Jianhua & Zhu, Donghua, 2018. "A technology delivery system for characterizing the supply side of technology emergence: Illustrated for Big Data & Analytics," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 165-176.
  8. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
  9. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
  10. Lu Huang & Yijie Cai & Erdong Zhao & Shengting Zhang & Yue Shu & Jiao Fan, 2022. "Measuring the interdisciplinarity of Information and Library Science interactions using citation analysis and semantic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6733-6761, November.
  11. 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).
  12. Zhang, Yi & Robinson, Douglas K.R. & Porter, Alan L. & Zhu, Donghua & Zhang, Guangquan & Lu, Jie, 2016. "Technology roadmapping for competitive technical intelligence," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 175-186.
  13. Jong Hwan Suh, 2019. "SocialTERM-Extractor: Identifying and Predicting Social-Problem-Specific Key Noun Terms from a Large Number of Online News Articles Using Text Mining and Machine Learning Techniques," Sustainability, MDPI, vol. 11(1), pages 1-44, January.
  14. 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.
  15. 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.
  16. Yi Zhang & Xiaojing Cai & Caroline V. Fry & Mengjia Wu & Caroline S. Wagner, 2021. "Topic evolution, disruption and resilience in early COVID-19 research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4225-4253, May.
  17. Zhang, Yi & Zhang, Guangquan & Chen, Hongshu & Porter, Alan L. & Zhu, Donghua & Lu, Jie, 2016. "Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 179-191.
  18. Song, Kisik & Kim, Karp Soo & Lee, Sungjoo, 2017. "Discovering new technology opportunities based on patents: Text-mining and F-term analysis," Technovation, Elsevier, vol. 60, pages 1-14.
  19. 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.
  20. 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.
  21. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  22. Yi Zhang & Yue Qian & Ying Huang & Ying Guo & Guangquan Zhang & Jie Lu, 2017. "An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1925-1946, June.
  23. Robinson, Douglas K.R. & Lagnau, Axel & Boon, Wouter P.C., 2019. "Innovation pathways in additive manufacturing: Methods for tracing emerging and branching paths from rapid prototyping to alternative applications," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 733-750.
  24. Ma, Jing & Abrams, Natalie F. & Porter, Alan L. & Zhu, Donghua & Farrell, Dorothy, 2019. "Identifying translational indicators and technology opportunities for nanomedical research using tech mining: The case of gold nanostructures," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 767-775.
  25. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
  26. Zhang, Yi & Shang, Lining & Huang, Lu & Porter, Alan L. & Zhang, Guangquan & Lu, Jie & Zhu, Donghua, 2016. "A hybrid similarity measure method for patent portfolio analysis," Journal of Informetrics, Elsevier, vol. 10(4), pages 1108-1130.
  27. Jing Ma & Yaohui Pan & Chih-Yi Su, 2022. "Organization-oriented technology opportunities analysis based on predicting patent networks: a case of Alzheimer’s disease," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5497-5517, September.
  28. Lee, Changyong, 2021. "A review of data analytics in technological forecasting," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
  29. Sun, Bixuan & Kolesnikov, Sergey & Goldstein, Anna & Chan, Gabriel, 2021. "A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
  30. 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).
  31. 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.
  32. Joung, Junegak & Kim, Kwangsoo, 2017. "Monitoring emerging technologies for technology planning using technical keyword based analysis from patent data," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 281-292.
  33. Lu Huang & Xiang Chen & Yi Zhang & Yihe Zhu & Suyi Li & Xingxing Ni, 2021. "Dynamic network analytics for recommending scientific collaborators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 8789-8814, November.
  34. 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).
  35. Stephen F. Carley & Nils C. Newman & Alan L. Porter & Jon G. Garner, 2018. "An indicator of technical emergence," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 35-49, April.
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