A deep learning-based model for patent portfolio recommendation leveraging overall and sequential features

Key Points

• 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.