信息资源管理学报2024，Vol.14Issue(6)：116-130,15.DOI:10.13365/j.jirm.2024.06.116
融合文本和引用特征的科学技术互动社区识别研究
Identification of Science and Technology Interaction Communities by Fusing Tex-tual and Citation Characteristics of Papers and Patents
摘要
Abstract
A good interaction pattern between science and technology is the key to generating major inno-vations,and exploring the identification method of science and technology interaction community fusing text and citation characteristics for scientific and technological innovations represented by papers and patents will help researchers and innovation managers to understand the interaction pattern of science and technology,optimize the transformation of scientific and technological innovations,and discover the path of scientific and technological cross-innovation.Based on the algorithms of text representation learning,graph autoencoder(GAE)and similarity network fusion(SNF),this study proposes a method to identify science and technology interaction communities by fusing textual and citation characteristics of papers and patents,and comprehen-sively analyzes the science and technology interactions in a specific field from the dimensions of content and intensity of interaction communities.In this study,the field of genetically engineered vaccines is selected for empirical analysis,and the effectiveness of the method is verified through comparative experiments.The re-sults show that the science and technology interaction communities identified in this study can effectively de-scribe the science and technology interaction situation in the field,demonstrate the hotspots of scientific and technological cross-innovation in the field as well as the evolution of interaction,restore the development of the science and technology interaction communities,and provide brand new knowledge units and application scenarios for the study of science and technology interaction.关键词
科学技术互动/社区发现/图自编码器/文本表示学习/网络融合Key words
Science and technology interaction/Community identification/Graph auto-encoder/Text representation learning/Network fusion引用本文复制引用
王嘉杰,侯万方,马亚雪,孙建军..融合文本和引用特征的科学技术互动社区识别研究[J].信息资源管理学报,2024,14(6):116-130,15.基金项目
本文系国家社科基金重大项目"前沿交叉领域识别与融合创新路径与预测方法研究"(23&ZD225)的研究成果之一.(This research is supported by the Major Project of the National Social Science Foundation,"Research on In-novation Paths and Prediction Methods for Identification and Integration of Frontier Cross-Disciplinary Fields"(23&ZD225).) （23&ZD225）
