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数据分析与知识发现  2021, Vol. 5 Issue (8): 122-131     https://doi.org/10.11925/infotech.2096-3467.2020.1122
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
人才多元评价模型设计方法研究*
徐曾旭林,谢靖(),于倩倩
中国科学院文献情报中心 北京 100190
中国科学院大学图书情报与档案管理系 北京 100190
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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摘要 

【目的】 构建多维化指标、多样化标准和多元化主体的人才评价模型。【方法】 围绕学术成果、科研项目、合作交流及产出应用,从学术贡献与科研潜力两方面设计量化指标。【结果】 本研究提出指标可组合、权重可调整的分类人才评价模型,并设计数据驱动下多主体参与的模型应用流程。【局限】 研究尚处于理论研究阶段,还未结合大规模数据开展完整的验证实验。【结论】 所提模型提供人才的多维画像与多元评价方法,有助于完善人才评审机制,营造激发创新的科研生态。

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徐曾旭林
谢靖
于倩倩
关键词 用户画像人才评价学术贡献科研潜力    
Abstract

[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
收稿日期: 2020-11-13      出版日期: 2021-09-15
ZTFLH:  G350  
基金资助:*国家科技图书文献中心下一代国家科技创新开放知识服务系统项目(科1810)
通讯作者: 谢靖 ORCID:0000-0001-6698-1786     E-mail: xiej@mail.las.ac.cn
引用本文:   
徐曾旭林, 谢靖, 于倩倩. 人才多元评价模型设计方法研究*[J]. 数据分析与知识发现, 2021, 5(8): 122-131.
Xu Zengxulin, Xie Jing, Yu Qianqian. Designing New Evaluation Model for Talents. Data Analysis and Knowledge Discovery, 2021, 5(8): 122-131.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2020.1122      或      http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2021/V5/I8/122
Fig.1  人才多元评价模型
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
G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
Table 1  人才评价指标体系
Fig.2  人才评价模型应用流程
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