现代情报2025，Vol.45Issue(6)：14-25,12.DOI:10.3969/j.issn.1008-0821.2025.06.002
基于异构图卷积网络的专利发明人潜在合作伙伴识别方法研究
Study on Identifying Potential Collaborators for Patent Inventors Based on Heterogeneous Graph Convolutional Networks
摘要
Abstract
[Purpose/Significance]Patent inventors often face information overload when seeking collaborators,and collaboration among patent inventors is frequently constrained by various practical factors.Identifying potential collaborators for patent inventors amidst vast amounts of information is a pressing issue that needs to be addressed at this stage.[Method/Process]This study constructed a collaboration network for patent inventors based on three layers of relationships:direct trust,indirect trust,and domain preferences.By integrating the content information of patent texts,a heterogeneous graph convolutional network was employed to identify potential collaborators for patent inventors,followed by a segmentation of these potential partners.[Result/Conclusion]Empirical analysis using patent data from the intelligent sensor field within the industrial internet demonstrates that the proposed method has strong practical application.The model's AUC,accuracy,precision,and recall rates significantly outperform baseline models.By identifying and segmenting potential collaborators for patent inventors,this approach provides targeted recommendations for collaboration,which facilitates resource sharing,complementary strengths,and enhances innovation efficiency.关键词
专利发明人/合作伙伴/识别方法/异构图卷积网络/合作信息/领域偏好/社交信任Key words
patent inventors/collaborators/identification/heterogeneous graph convolutional network/collabora-tion information/domain preferences/social trust引用本文复制引用
谢小东,吴洁,盛永祥,唐健廷..基于异构图卷积网络的专利发明人潜在合作伙伴识别方法研究[J].现代情报,2025,45(6):14-25,12.基金项目
国家自然科学基金面上项目"面向产业安全的产业创新生态系统韧性内涵、评价与优化策略研究"(项目编号:72171122) （项目编号:72171122）
江苏省研究生科研与实践创新计划项目"创新联合体潜在合作伙伴选择及合作方向研究"(项目编号:KYCX23_3817). （项目编号:KYCX23_3817）
