ARCHIVES
Original Article
A Data-Driven Machine Learning Framework for Assessing Patent Commercial Value and Technological Significance
K. N. Kavya1
1 Department of CSE (Data Science), RNS Institute of Technology, Bengaluru, Karnataka, India.
Published Online: January-February 2026
Pages: 30-38
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260701003
References
1. Q. Zhang, Q. Yu, Y. Tian, Automated Patent Evaluation Using Machine Learning Techniques: A Comprehensive Review, Journal of Intellectual Property Research, 10(3), 2023, 45–62.
2. H. Chen, L. Wang, Y. Liu, Deep Learning-Based Approach for Patent Evaluation: A Comparative Study, Expert Systems with Applications, 165, 2023, 113842.
3. S. Kim, J. Park, S. Lee, Ensemble Learning Techniques for Patent Valuation: A Comparative Analysis, Information Processing and Management, 59(1), 2023, 102635.
4. X. Li, Y. Zhang, H. Wang, Predicting Patent Value Using Text Mining and Machine Learning: A Case Study in Biotechnology, World Patent Information, 71, 2022, 101988.
5. J. Wu, C. Cheng, L. Li, Enhancing Patent Evaluation with Graph Neural Networks, Neural Computing and Applications, 2022, 1–12.
6. Gupta, V. Singh, R. Sharma, Hybrid Model for Patent Valuation Using Deep Learning and Sentiment Analysis, Journal of Intelligent Manufacturing, 2022, 1–13.
7. Y. Ma, M. Liu, Z. Hu, Incorporating Temporal Features into Machine Learning Models for Patent Valuation, Journal of Informetrics, 16(1), 2022, 101194.
8. Y. Sun, J. Wang, Z. Zhang, Predicting Patent Litigation Using Machine Learning: A Comparative Study, Journal of Empirical Legal Studies, 19(4), 2022, 856–879.
9. X. Yang, L. Zhang, H. Liu, Hybrid Machine Learning Model for Patent Evaluation: A Case Study in the Semiconductor Industry, IEEE Transactions on Engineering Management, 68(4), 2021, 1097–1108.
10. Zhao, Z. Li, Y. Wang, Predicting Patent Commercialization Success Using Machine Learning: A Longitudinal Study, Technological Forecasting and Social Change, 174, 2021, 121402.
11. Q. Liu, M. Zhou, L. Wu, Patent Evaluation with Attention Mechanism-Based Deep Learning Models, Information Sciences, 601, 2021, 101–113.
12. H. Zhang, X. Huang, X. Wang, Exploring Patent Portfolio Diversification Using Machine Learning Techniques, Scientometrics, 127(1), 2021, 101–120.
13. Y. Wang, Q. Zhang, Y. Liu, Predicting Patent Citations Using Deep Learning Models: A Comparative Analysis, Journal of Data and Information Science, 6(3), 2021, 325–339.
14. S. Chen, W. Li, L. Liu, Machine Learning-Based Patent Classification for Technology Landscape Analysis, Scientometrics, 125(3), 2020, 1981–2000.
15. S. Park, J. Kim, H. Lee, A Novel Approach for Patent Evaluation Using Graph Convolutional Networks, Expert Systems with Applications, 152, 2020, 113357.
16. D. Rotolo, D. Hicks, B. R. Martin, What is an emerging technology?, Research Policy, 44(10), 2015, 1827–1843.
17. D. Verhoeven, S. Bakker, R. Veugelers, B. van der Zwaan, Designing a new classification of technologies, Research Policy, 45(2), 2016, 379–389.
18. Y. Noh, S. Kang, J. Lee, Identifying promising technologies based on patent data: Case of nanotechnology, Technological Forecasting and Social Change, 106, 2016, 121–130.
19. M. Song, J. Lee, S. Min, Identifying emerging technologies using text mining: A case of dye-sensitized solar cells, Technological Forecasting and Social Change, 123, 2017, 118–130.
20. U. Daim, G. Rueda, H. Martin, N. Gerdsri, Forecasting emerging technologies: Use of bibliometrics and patent analysis, Technological Forecasting and Social Change, 73(8), 2006, 981–1012.
21. Yoon, Morphological analysis for identifying technological impacts: Application to RFID technology, Technological Forecasting and Social Change, 75(5), 2008, 619–633.
22. J. Kim, H. Seol, Identifying core technologies using patent information: A systematic method, Expert Systems with Applications, 39(10), 2012, 8862–8870.
23. H. Park, K. Kim, E. Jeong, Technology portfolio management using collaborative filtering approach, Technovation, 27(7), 2007, 387–399.
24. J. Joung, Y. Kim, Emerging technology monitoring based on patent keyword analysis, Journal of Intelligence Studies in Business, 7(2), 2017, 5–15.
25. Li, Y. Zheng, Y. Li, X. Liang, A novel framework for monitoring the development trend of emerging technologies, Information Processing and Management, 54(5), 2018, 770–784.
26. V. Trappey, A. J. C. Trappey, Y. C. Lai, Applying neural network with PCA to classify patents by their im- portance: A study of cross-border data communications technology, Expert Systems with Applications, 39(8), 2012, 7260–7269.
27. M. Kyebambe, Y. Tang, G. Zhang, Identification of promising technologies using patent citation and text data, Journal of Informetrics, 11(4), 2017, 1235–1252.
28. W. J. Lee, D. Y. Kim, H. Y. Park, A supervised machine learning approach to identifying emerging technologies based on patent data, Technological Forecasting and Social Change, 129, 2018, 257–264.
2. H. Chen, L. Wang, Y. Liu, Deep Learning-Based Approach for Patent Evaluation: A Comparative Study, Expert Systems with Applications, 165, 2023, 113842.
3. S. Kim, J. Park, S. Lee, Ensemble Learning Techniques for Patent Valuation: A Comparative Analysis, Information Processing and Management, 59(1), 2023, 102635.
4. X. Li, Y. Zhang, H. Wang, Predicting Patent Value Using Text Mining and Machine Learning: A Case Study in Biotechnology, World Patent Information, 71, 2022, 101988.
5. J. Wu, C. Cheng, L. Li, Enhancing Patent Evaluation with Graph Neural Networks, Neural Computing and Applications, 2022, 1–12.
6. Gupta, V. Singh, R. Sharma, Hybrid Model for Patent Valuation Using Deep Learning and Sentiment Analysis, Journal of Intelligent Manufacturing, 2022, 1–13.
7. Y. Ma, M. Liu, Z. Hu, Incorporating Temporal Features into Machine Learning Models for Patent Valuation, Journal of Informetrics, 16(1), 2022, 101194.
8. Y. Sun, J. Wang, Z. Zhang, Predicting Patent Litigation Using Machine Learning: A Comparative Study, Journal of Empirical Legal Studies, 19(4), 2022, 856–879.
9. X. Yang, L. Zhang, H. Liu, Hybrid Machine Learning Model for Patent Evaluation: A Case Study in the Semiconductor Industry, IEEE Transactions on Engineering Management, 68(4), 2021, 1097–1108.
10. Zhao, Z. Li, Y. Wang, Predicting Patent Commercialization Success Using Machine Learning: A Longitudinal Study, Technological Forecasting and Social Change, 174, 2021, 121402.
11. Q. Liu, M. Zhou, L. Wu, Patent Evaluation with Attention Mechanism-Based Deep Learning Models, Information Sciences, 601, 2021, 101–113.
12. H. Zhang, X. Huang, X. Wang, Exploring Patent Portfolio Diversification Using Machine Learning Techniques, Scientometrics, 127(1), 2021, 101–120.
13. Y. Wang, Q. Zhang, Y. Liu, Predicting Patent Citations Using Deep Learning Models: A Comparative Analysis, Journal of Data and Information Science, 6(3), 2021, 325–339.
14. S. Chen, W. Li, L. Liu, Machine Learning-Based Patent Classification for Technology Landscape Analysis, Scientometrics, 125(3), 2020, 1981–2000.
15. S. Park, J. Kim, H. Lee, A Novel Approach for Patent Evaluation Using Graph Convolutional Networks, Expert Systems with Applications, 152, 2020, 113357.
16. D. Rotolo, D. Hicks, B. R. Martin, What is an emerging technology?, Research Policy, 44(10), 2015, 1827–1843.
17. D. Verhoeven, S. Bakker, R. Veugelers, B. van der Zwaan, Designing a new classification of technologies, Research Policy, 45(2), 2016, 379–389.
18. Y. Noh, S. Kang, J. Lee, Identifying promising technologies based on patent data: Case of nanotechnology, Technological Forecasting and Social Change, 106, 2016, 121–130.
19. M. Song, J. Lee, S. Min, Identifying emerging technologies using text mining: A case of dye-sensitized solar cells, Technological Forecasting and Social Change, 123, 2017, 118–130.
20. U. Daim, G. Rueda, H. Martin, N. Gerdsri, Forecasting emerging technologies: Use of bibliometrics and patent analysis, Technological Forecasting and Social Change, 73(8), 2006, 981–1012.
21. Yoon, Morphological analysis for identifying technological impacts: Application to RFID technology, Technological Forecasting and Social Change, 75(5), 2008, 619–633.
22. J. Kim, H. Seol, Identifying core technologies using patent information: A systematic method, Expert Systems with Applications, 39(10), 2012, 8862–8870.
23. H. Park, K. Kim, E. Jeong, Technology portfolio management using collaborative filtering approach, Technovation, 27(7), 2007, 387–399.
24. J. Joung, Y. Kim, Emerging technology monitoring based on patent keyword analysis, Journal of Intelligence Studies in Business, 7(2), 2017, 5–15.
25. Li, Y. Zheng, Y. Li, X. Liang, A novel framework for monitoring the development trend of emerging technologies, Information Processing and Management, 54(5), 2018, 770–784.
26. V. Trappey, A. J. C. Trappey, Y. C. Lai, Applying neural network with PCA to classify patents by their im- portance: A study of cross-border data communications technology, Expert Systems with Applications, 39(8), 2012, 7260–7269.
27. M. Kyebambe, Y. Tang, G. Zhang, Identification of promising technologies using patent citation and text data, Journal of Informetrics, 11(4), 2017, 1235–1252.
28. W. J. Lee, D. Y. Kim, H. Y. Park, A supervised machine learning approach to identifying emerging technologies based on patent data, Technological Forecasting and Social Change, 129, 2018, 257–264.
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