Using the node importance of patent network to evaluate patent relational value

Area of Science:

• Network Science
• Intellectual Property Management
• Bibliometrics

Background:

• Patent citation networks are crucial for evaluating technology value.
• Existing centrality measures often overlook the structural context of neighboring patents.
• A need exists for improved methods to assess patent relational value.

Purpose of the Study:

• To propose a novel index, the Patent Node Importance Index (PNII), for evaluating patent relational value.
• To incorporate local network structural information into patent value assessment.
• To compare the effectiveness of PNII against traditional centrality measures.

Main Methods:

• Construction of a comprehensive patent citation network.
• Definition and calculation of structural importance based on patent similarity and "node pairs" (neighboring patents and their neighbors).
• Application of the SIR model to assess patent propagation influence for comparative analysis.

Main Results:

• The proposed PNII effectively captures the structural importance of patents within the citation network.
• PNII demonstrates superior accuracy and scientific rigor in evaluating patent relational value compared to general network centralities.
• Analysis using the SIR model validates the enhanced evaluation capabilities of PNII.

Conclusions:

• The PNII offers a more scientific and accurate method for patent value evaluation by considering network structure.
• Network science principles can significantly enhance traditional patent analysis.
• This approach provides a valuable tool for understanding patent importance and technological relationships.