RESEARCH PAPERS

Identification of Transferable University Patents Based on Research Team Features

  • YU Yan ,
  • LIU Pan ,
  • XUE Liujun
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  • 1 Nanjing Tech University Library, Nanjing 211816;
    2 School of Economics and Management, Nanjing Tech University, Nanjing 211816
Yu Yan, Professor, PhD, Master's Supervisor, E-mail:yuyanyuyan2004@126.com; Liu Pan, Master's Candidate; Xue Liujun, Master's Candidate.

Received date: 2025-03-17

  Revised date: 2025-08-16

  Online published: 2026-06-23

Supported by

This work is supported by the project of National Social Science Fund of China, titled “Research on the Construction of a Data-Driven SupplyDemand Information Mining Model for University Technology Transfer” (Grant No. 23BTQ098).

Abstract

[Purpose/Significance] Current methods for identifying transferable university patents face challenges in accurately constructing inventor features, particularly for patents with multiple inventors. This study proposes a research team feature-based approach to improve the identification accuracy. [Method/Process] First, an optimized label propagation algorithm is used to identify university research teams. Then, based on the identified teams, a method for constructing research team features centered on core members is proposed. Finally, these team features is integrated into a machine learning model to identify transferable patents, and the SHAP model along with decision rules are employed to interpret the results. [Result/Conclusion] The effectiveness of the proposed method is validated through experiments on patent transfer data from Nanjing Tech University and Stanford University. This approach provides technical support for the transferable university patents.

Cite this article

YU Yan , LIU Pan , XUE Liujun . Identification of Transferable University Patents Based on Research Team Features[J]. Library and Information Service, 2026 , 70(13) : 16 -30 . DOI: 10.13266/j.issn.0252-3116.2026.13.002

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