PatentSBERTa: A deep NLP based hybrid model for patent distance and classification using augmented SBERT
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DOI: 10.1016/j.techfore.2024.123536
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- Jeff Alstott & Giorgio Triulzi & Bowen Yan & Jianxi Luo, 2017. "Mapping technology space by normalizing patent networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(1), pages 443-479, January.
- Duen-Ren Liu & Meng-Jung Shih, 2011. "Hybrid-patent classification based on patent-network analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(2), pages 246-256, February.
- Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1993.
"Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations,"
The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(3), pages 577-598.
- Adam B. Jaffe & Manuel Trajtenberg & Rebecca Henderson, 1992. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," NBER Working Papers 3993, National Bureau of Economic Research, Inc.
- Jaffe, A.B. & Trajtenberg, M., 1992. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," Papers 14-92, Tel Aviv.
- Yuan Zhou & Fang Dong & Yufei Liu & Zhaofu Li & JunFei Du & Li Zhang, 2020. "Forecasting emerging technologies using data augmentation and deep learning," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 1-29, April.
- Arts, Sam & Hou, Jianan & Gomez, Juan Carlos, 2021. "Natural language processing to identify the creation and impact of new technologies in patent text: Code, data, and new measures," Research Policy, Elsevier, vol. 50(2).
- Shaobo Li & Jie Hu & Yuxin Cui & Jianjun Hu, 2018. "DeepPatent: patent classification with convolutional neural networks and word embedding," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 721-744, November.
- Aharonson, Barak S. & Schilling, Melissa A., 2016. "Mapping the technological landscape: Measuring technology distance, technological footprints, and technology evolution," Research Policy, Elsevier, vol. 45(1), pages 81-96.
- Jie Hu & Shaobo Li & Jianjun Hu & Guanci Yang, 2018. "A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
- Sam Arts & Bruno Cassiman & Juan Carlos Gomez, 2018.
"Text matching to measure patent similarity,"
Strategic Management Journal, Wiley Blackwell, vol. 39(1), pages 62-84, January.
- Sam Arts & Bruno Cassiman & Juan Carlos Gomez, 2017. "Text matching to measure patent similarity," Working Papers of Department of Management, Strategy and Innovation, Leuven 590543, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
- 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.
- Breschi, Stefano & Lissoni, Francesco & Malerba, Franco, 2003. "Knowledge-relatedness in firm technological diversification," Research Policy, Elsevier, vol. 32(1), pages 69-87, January.
- Dieter F. Kogler & David L. Rigby & Isaac Tucker, 2013. "Mapping Knowledge Space and Technological Relatedness in US Cities," European Planning Studies, Taylor & Francis Journals, vol. 21(9), pages 1374-1391, September.
- Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
- Trappey, Amy & Trappey, Charles V. & Hsieh, Alex, 2021. "An intelligent patent recommender adopting machine learning approach for natural language processing: A case study for smart machinery technology mining," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
- 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).
- Hain, Daniel S. & Jurowetzki, Roman & Buchmann, Tobias & Wolf, Patrick, 2022. "A text-embedding-based approach to measuring patent-to-patent technological similarity," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
- Zhen-Wu Wang & Si-Kai Wang & Ben-Ting Wan & William Wei Song, 2020. "A novel multi-label classification algorithm based on K-nearest neighbor and random walk," International Journal of Distributed Sensor Networks, , vol. 16(3), pages 15501477209, March.
- WANG, La-yin & ZHAO, Dong, 2021. "Cross-domain function analysis and trend study in Chinese construction industry based on patent semantic analysis," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
- Ma, Tingting & Zhou, Xiao & Liu, Jia & Lou, Zhenkai & Hua, Zhaoting & Wang, Ruitao, 2021. "Combining topic modeling and SAO semantic analysis to identify technological opportunities of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
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Keywords
Technological distance; Patent classification; Deep NLP; Augmented SBERT; Hybrid model; Model explainability;All these keywords.
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