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A deep learning-based model for patent portfolio recommendation leveraging overall and sequential features | Synapse
March 3, 2026
A deep learning-based model for patent portfolio recommendation leveraging overall and sequential features
MX
Manru Xu
Hefei University of Technology
JS
Jianshan Sun
Ministry of Education of the People's Republic of China
HL
Haifeng Ling
Ministry of Education of the People's Republic of China
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Puntos clave
The model provides effective patent portfolio recommendations, enhancing decision-making processes.
Using a deep learning approach, the model capitalizes on overall and sequential features to optimize recommendations.
Observational analysis highlighted the model's utility in managing extensive patent information, benefiting innovators.
The findings may enable better alignment of patent strategies and innovation outcomes, though further validation is needed.
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Cite This Study
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Xu et al. (Mon,) studied this question.
synapsesocial.com/papers/69a765b9badf0bb9e87da2fb
https://doi.org/https://doi.org/10.1007/s11192-026-05554-9