数字图书馆论坛2025，Vol.21Issue(9)：16-27,12.DOI:10.3772/j.issn.1673-2286.2025.09.003
基于特征测度和SciBERT模型的突破性科学创新主题识别研究
Breakthrough Scientific Innovation Topic Identification Based on Feature Measure and SciBERT Model:A Case Study of Agricultural Robots Field
摘要
Abstract
Breakthrough scientific innovation is the core driving force behind technological progress and socio-economic development.Accurately identifying breakthrough scientific innovations is of great significance for opening up new tracks of scientific and technological innovation and achieving leapfrog development.Starting from the characteristics of breakthrough scientific innovations in scientific paper data,we first comprehensively consider the diversity,balance,and difference of papers,using the True Diversity measurement index and disciplinary co-occurrence network to measure and screen potential papers.Then,we employ the SciBERT+K-means+UMAP method for topic modeling and visualization.From the four dimensions of novelty,content transformation,influence,and abruptness,we construct a multi-feature breakthrough scientific innovation indicator system,integrating various text mining methods to identify breakthrough scientific innovation topics.Taking the field of agricultural robots as an example,four breakthrough scientific innovation topics are ultimately identified:multimodal perception and adaptive intelligent decision-making,bio-inspired actuation and heterogeneous energy coupling for robots,swarm collaboration and cloud-edge-end architectural technology,and high-precision trajectory control and high-dynamic response.The effectiveness and reliability of the model are verified.The research not only provides new ideas for identifying breakthrough scientific innovation topics,but also provides a reference basis for original innovation in the field of smart agriculture.关键词
突破性科学创新/主题识别/农业机器人/机器学习/跨学科研究/SciBERT/K-meansKey words
Breakthrough Scientific Innovation/Topic Identification/Agricultural Robot/Machine Learning/Interdisciplinary Research/SciBERT/K-means分类
社会科学引用本文复制引用
QI ShiJie,CHUAN LiMin,ZHANG Hui,YAO Ru,JIA Qian,ZHAO JingJuan..基于特征测度和SciBERT模型的突破性科学创新主题识别研究[J].数字图书馆论坛,2025,21(9):16-27,12.基金项目
本研究得到北京市农林科学院科技创新能力建设专项"智库型农业情报研究与服务能力提升"(编号:KJCX20230208)、北京市农林科学院科技创新能力建设专项"面向科研管理的情报研究与服务能力提升"(编号:KJCX20230210)资助. （编号:KJCX20230208）
