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Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (8): 122-131    DOI: 10.11925/infotech.2096-3467.2020.1122
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Designing New Evaluation Model for Talents
Xu Zengxulin,Xie Jing(),Yu Qianqian
National Science Library, Chinese Academy of Sciences, Beijing 100190, China
Department of Library, Information and Archives Management, University of Chinese Academy of Sciences, Beijing 100190, China
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[Objective] This paper proposes a talent evaluation model with multi-dimensional indicators, as well as diversified standards and subjects. [Methods] We designed quantitative indicators from the perspectives of academic contribution and research potential based on scholarly achievements, research projects, peer cooperation, and practical applications. [Results] The proposed model could combine indicators and adjust their weights. We also designed a data-driven procedures for the multi-agent participated model. [Limitations] This research is still in the theoretical development stage and requires more experiment with large-scale data. [Conclusions] Our model provides multi-dimensional portraits and evaluation methods for talents, which improves the evaluation mechanism and creates an academic ecosystem for innovation.

Key wordsUser Portrait      Talent Evaluation      Academic Contribution      Scientific Research Potential     
Received: 13 November 2020      Published: 15 September 2021
ZTFLH:  G350  
Fund:Next-generation National Science and Technology Innovation Open Knowledge Service System Project of the National Science and Technology Library(科1810)
Corresponding Authors: Xie Jing ORCID:0000-0001-6698-1786     E-mail:

Cite this article:

Xu Zengxulin, Xie Jing, Yu Qianqian. Designing New Evaluation Model for Talents. Data Analysis and Knowledge Discovery, 2021, 5(8): 122-131.

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Diversified Talent Evaluation Model
一级指标 二级指标 三级指标
学术贡献指标 成果数量 nu m res 期刊论文数量 nu m p
会议活动数量 nu m c
项目承担数量 nu m p 1
专利获得数量 nu m p 2
成果被引量 ef f res 期刊论文被引量 ci t p
会议报告被引量 ci t c
专利申请被引量 ci t p 2
混合量化指标 mi x res H指数
期刊论文综合价值 In f 1 期刊影响因子 IF
作者位序 ran k p
会议活动综合价值 In f 2 会议级别 Lev
作者位序 ran k c
报告类型 weig h t c
项目承担综合价值 In f 3 科研项目级别 weig h t lev
资助资金 nu m m
项目负责人 weig h t p
专利获得综合价值 In f 4 专利类型 weig h t d
发明人位序 ran k p 2
科研潜力指标 学术社交性指数 Soc T 合著成果数 nu m co
合著者影响力 Inf co
团队组织因子 weig h t co
科研活跃性指数 Act T n年的学术影响力 Inf ( T n )
学术多样性指数 Div T 研究主题分布 P T t
科研成果转化率指数 Con T 项目-论文转化度 r p , 1
项目-专利转化度 r p , 2
项目产出权重占比 w p
Talent Evaluation Index System
Application Process of Talent Evaluation Model
[1] 中华人民共和国中央人民政府. 科技部教育部人力资源社会保障部中科院工程院关于开展清理“唯论文、唯职称、唯学历、唯奖项”专项行动的通知[EB/OL]. [2020-10-27].
[1] (The Central People’s Government of the People’s Republic of China. Ministry of Science and Technology, Ministry of Education, Ministry of Human Resources and Social Security, Chinese Academy of Sciences, Ministry of Engineering, Notice on Launching the Special Action to Clean Up “Only Papers, TitlesOnly, Only Educational Backgrounds, and Only Awards” [EB/OL]. [2020-10-27].
[2] 中华人民共和国科学技术部. 关于破除科技评价中“唯论文”不良导向的若干措施(试行) [EB/OL]. [2020-05-25].
[2] (Ministry of Science and Technology of the People’s Republic of China. Measures to Eliminate the “Paper-Only” Bad Orientation in Scientific and Technological Evaluation (for Trial Implementation) [EB/OL]. [2020-05-25].
[3] 中华人民共和国教育部. 教育部科技部印发《关于规范高等学校SCI论文相关指标使用树立正确评价导向的若干意见》的通知 [EB/OL]. [2020-05-25].
[3] (Ministry of Education of the People’s Republic of China. Ministry of Education, Ministry of Science and Technology Issue Several Opinions on Regulating the Use of Related Indicators of SCI Papers in Colleges and Universities and Establishing Correct Evaluation Orientation Notice [EB/OL]. [2020-05-25].
[4] 刘志强, 陈旭婻. 科研人才评估研究——基于国内外先进经验的借鉴[J]. 科技与创新, 2020(23):92-93, 96.
[4] ( Liu Zhiqiang, Chen Xunan. Research on the Evaluation of Scientific Research Talents——Based on the Integration of Domestic and Foreign Advanced Experience[J]. Science and Technology & Innovation, 2020(23):92-93, 96.)
[5] 刘智群, 李颖, 安凤妹. 科学计量指标在科研人员评价中应用[J]. 科技管理研究, 2011 (14):79-82.
[5] ( Liu Zhiqun, Li Ying, An Fengmei. Statistical Analysis of Papers on Medical Informatics in China[J]. Science and Technology Management Research, 2011 (14):79-82.)
[6] 王婷, 伊雷, 张智萍, 等. 基于文献计量的高层次科研人才发现服务体系构建——以北京化工大学为例[J]. 情报探索, 2015 (7):7-11.
[6] ( Wang Ting, Yi Lei, Zhang Zhiping, et al. Bibliometrics-based Construction of Service System for High-level Scientific Talent Discovery: Case Study of Beijing University of Chemical Technology[J]. Information Research, 2015(7):7-11.)
[7] 李远明, 余慈爱, 王文兵. 高校领军人才发现与评价——图书馆学科服务实践探索[J]. 现代情报, 2012, 32(11):34-38.
[7] ( Li Yuanming, Yu Ciai, Wang Wenbing. On the Discovery and Evaluation of Universities' Leading Talents——Exploration of Library Subject Service Practice[J]. Journal of Modern Information, 2012, 32(11):34-38.)
[8] 杨锴, 赵希男. 高层次科技人才创新能力识别及团队构建[J]. 中国科技论坛, 2018 (11):141-150.
[8] ( Yang Kai, Zhao Xi’nan. Innovation Capacity Identification and Team Construction of High-Level Sci-Tech Talents[J]. Forum on Science and Technology in China, 2018(11):141-150.)
[9] 刘颖. 构建多元化创新科技人才评价体系[J]. 中国行政管理, 2019(5):90-95.
[9] ( Liu Ying. Constructing a Diversified Innovation-oriented Assessment System for Science and Technology Talents[J]. Chinese Public Administration, 2019(5):90-95.)
[10] 邵沚葭, 郝燕君, 陈丽丽. 基于AHP、熵权法最优集成的高校人才评价体系[J]. 中国管理信息化, 2019, 22(3):200-202.
[10] ( Shao Zhijia, Hao Yanjun, Chen Lili. University Talent Evaluation System Based on the Optimal Integration of AHP and Entropy Method[J]. China Management Informationization, 2019, 22(3):200-202.)
[11] 彭珍, 贺德方, 彭洁, 等. 以质量为导向的科技人才评价发现机制研究[J]. 科技管理研究, 2015, 35(9):53-55, 61.
[11] ( Peng Zhen, He Defang, Peng Jie, et al. Research on Quality Oriented Evaluation and Discovery Mechanism of Scientific and Technical Talents[J]. Science and Technology Management Research, 2015, 35(9):53-55, 61.)
[12] Li X L, Foo C S, Tew K L, et al. Searching for Rising Stars in Bibliography Networks[C]// Proceedings of the 14th International Conference on Database Systems for Advanced Applications. Springer, 2009: 288-292.
[13] Panagopoulos G, Tsatsaronis G, Varlamis I. Detecting Rising Stars in Dynamic Collaborative Networks[J]. Journal of Informetrics, 2017, 11(1):198-222.
doi: 10.1016/j.joi.2016.11.003
[14] Ning Z L, Liu Y Q, Kong X J. Social Gene — A New Method to Find Rising Stars[C]// Proceedings of 2017 International Symposium on Networks, Computers and Communications (ISNCC). IEEE, 2017. DOI: 10.1109/ISNCC.2017.8072031.
doi: 10.1109/ISNCC.2017.8072031
[15] Wang Z, Tang J, Gao B. How We Calculate Academic Statistics for an Expert? [EB/OL]. [2020-08-16].
[16] Hirsch J E. An Index to Quantify an Individual’s Scientific Research Output[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(46):16569-16572.
pmid: 16275915
[17] Egghe L. Theory and Practise of the g-Index[J]. Entometrics, 2006, 69(1):131-152.
[18] 周白瑜, 李佳蔚, 段春波, 等. 科研论文作者署名及排序的几点思考[J]. 科技与出版, 2020(2):106-110.
[18] ( Zhou Baiyu, Li Jiawei, Duan Chunbo, et al. Some Thoughts on the Author’s Signature and Ranking of Scientific Research Papers[J]. Science-Technology & Publication, 2020(2):106-110.)
[19] 刘威. 高校院系科研绩效综合评价与优化研究[D]. 保定: 华北电力大学, 2015.
[19] ( Liu Wei. Study on Multi-aspects Research Performance Assessment and Optimization for University Colleges and Departments[D]. Baoding: North China Electric Power University, 2015.)
[20] 王思培, 韩涛. 基于随机森林算法的潜在高价值专利预测方法研究[J]. 情报科学, 2020, 38(5):120-125.
[20] ( Wang Sipei, Han Tao. Prediction Method of Potential High-value Patents Based on Random Forest Algorithm[J]. Information Science, 2020, 38(5):120-125.)
[21] 吕晓蓉. 专利价值评估指标体系与专利技术质量评价实证研究[J]. 科技进步与对策, 2014, 31(20):113-116.
[21] ( Lv Xiaorong. Empirical Research on Patent Value Evaluation Index System and Patent Technology Quality Evaluation[J]. Science & Technology Progress and Policy, 2014, 31(20):113-116.)
[22] 周朝阳, 贺艳菊, 柳路芳. 融合合著者多样性及影响力的学术新星预测方法[J]. 情报理论与实践, 2020, 43(2):78-83, 71.
[22] ( Zhou Chaoyang, He Yanju, Liu Lufang. A Method for Predicting Rising Stars by Combining Co-Authors’ Diversity and Influence[J]. Information Studies: Theory & Application, 2020, 43(2):78-83, 71.)
[23] 袁康, 王颖, 缪园, 等. 导师科研活跃度和学术地位对博士生科研绩效的影响[J]. 学位与研究生教育, 2016(7):66-71.
[23] ( Yuan Kang, Wang Ying, Miao Yuan, et al. The Influence of Supervisor’s Research Activity and Academic Status on Doctoral Students' Research Performance[J]. Academic Degrees & Graduate Education, 2016(7):66-71.)
[24] Amjad T, Daud A, Song M. Measuring the Impact of Topic Drift in Scholarly Networks[C]// Proceedings of Conference on World Wide Web. 2018: 373-378.
[25] Zeng A, Shen Z S, Zhou J L, et al. Increasing Trend of Scientists to Switch Between Topics[J]. Nature Communications, 2019, 10:3439.
doi: 10.1038/s41467-019-11401-8 pmid: 31366884
[26] Brillouin L, Hellwarth R W. Science and Information Theory[J]. Physics Today, 1956, 9(12):39-40.
[27] 姚占雷, 陈红伶, 许鑫. 科研人才分类分级评价研究[J]. 西南民族大学学报(人文社科版), 2020, 41(6):234-240.
[27] ( Yao Zhanlei, Chen Hongling, Xu Xin. Study on the Classification and Evaluation of Scientific Research Talents[J]. Journal of Southwest University for Nationalities, 2020, 41(6):234-240.)
[28] 孔贝贝, 谢靖, 钱力, 等. 科技大数据增值丰富化方法研究与工具研发[J]. 数据分析与知识发现, 2019, 3(7):113-122.
[28] ( Kong Beibei, Xie Jing, Qian Li, et al. Methodology and Tools to Enrich Sci-Tech Big Data[J]. Data Analysis and Knowledge Discovery, 2019, 3(7):113-122.)
[29] 张建勇, 于倩倩, 黄永文, 等. NSTL统一文献元数据标准的设计与思考[J]. 数字图书馆论坛, 2016(2):33-38.
[29] ( Zhang Jianyong, Yu Qianqian, Huang Yongwen, et al. Metadata Standard Design of NSTL Unified Literature[J]. Digital Library Forum, 2016(2):33-38.)
[30] 光明日报. “立”起多元专业评价, 才能真正破除“唯论文”. [EB/OL].[2020-12-21].
[30] (Guang Ming Daily. Only by ‘Establishing’ Multiple Professional Evaluations can We Truly Get Rid of ‘Thesis Only’[EB/OL].[2020-12-21].
[31] 杨月坤, 查椰. 国外科技人才评价经验的启示与借鉴——基于英国、美国、德国的研究[J]. 科学管理研究, 2020, 38(1):160-165.
[31] ( Yang Yuekun, Zha Ye. Enlightenment and Reference from the Experience of Foreign Scientific and Technological Talents: A Study Based on Britain, the United States and Germany[J]. Scientific Management Research, 2020, 38(1):160-165.)
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