摘要
本研究以中国科学院科技专家库建设为案例,探讨了在信息安全环境下利用智能技术完善并更新专家库信息、运用综合指标遴选专家的路径,在此基础上总结了中科院科技专家库信息系统的设计与实践。首先,基于Python大数据网络爬虫技术和文献情报分析相结合的方式,补充专家基础数据,并定期更新专家信息;其次,建立专家信誉度评价指标体系;第三,在遴选专家时,运用TF-IDF算法对项目和专家信息进行关联分析,并结合学科分类标准对专家研究领域分类,以提高项目-专家研究领域的匹配度;第四,综合各项关键指标遴选确定最终候选专家;最后,在此基础上设计并开发了中科院科技专家库信息系统,有效提升了专家库管理和专家遴选的工作效率。
By taking the construction of the science and technology expert database of Chinese Academy of Sciences as the case,the study explored the path of using intelligent technology to improve and update the expert database information and using the comprehensive index in the information security environment,and on the basis of this,summarized the design and practice of information system of the science and technology expert database,Chinese Academy of Sciences.Firstly,based on the combination of the Python big data web crawler technology and literature information analysis,the expert basic data is supplemented and the expert information was updated regularly.Secondly,the expert credibility evaluation index system was established;Thirdly,in the selection of experts,TF-IDF algorithm was used to analyze the correlation between project and expert information,and the expert research field was classified according to the discipline classification standard to improve the matching degree between project and expert research field.Fourthly,the final candidate experts were selected based on various key indicators.Finally,on this basis,science and technology expert database information system of Chinese Academy of Sciences was designed and developed,which effectively improved the efficiency of expert database management and expert selection.
作者
杨好
周长海
Yang Hao;Zhou Changhai(Institutes of Science and Development,Chinese Academy of Sciences,Beijing 100190;Bureau of Development and Planning,Chinese Academy of Sciences,Beijing 100864)
出处
《科技促进发展》
2022年第7期864-871,共8页
Science & Technology for Development
关键词
科技专家库
Python技术
TF-IDF算法
专家遴选
专家库信息系统
science and technology expert database
python technology
TF-IDF algorithm
expert selected
expert database information system
作者简介
杨好,硕士,研究方向:计算机科学技术在科技评价中的应用,数据分析、数据库与信息管理技术以及研究所评价等;通讯作者:周长海,博士,副处长,研究方向:科技评价与科技政策,科研机构评价,科技成果评价和奖励评审等。
