GLE: an important patentee identification method based on comprehensive structural entropy

Key Points

• The research aims to identify important methods for detecting patentees through structural entropy analysis.
• Utilized comprehensive structural entropy to analyze patent data.
• Developed a framework for identifying potential patentees.
• Examined the effectiveness of the method in various fields including technology and environmental sciences.
• Demonstrated significant improvement in patentee identification accuracy with structural entropy analysis.
• Reported an effect size indicating strong validation of the method's applicability in diverse sectors.