首页|融合创新性与影响力的论文代表作遴选方法研究

融合创新性与影响力的论文代表作遴选方法研究

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[目的]综合考虑论文的创新性和影响力,提出一种新的论文代表作遴选方法.[方法]基于论文创新性和影响力测度指标,设计代表性指数,遴选代表性指数靠前的论文作为学者的论文代表作.以诺贝尔物理学奖获得者为例,遴选其论文代表作,将平均排名和准确率作为评价指标检验遴选方法的有效性和准确性.选取张涛院士和Hirsch J E教授进行案例分析,使用代表性指数遴选其论文代表作.[结果]实证结果表明,与其他6种遴选方法对比,使用代表性指数遴选论文代表作在平均排名(2.838)和准确率(63.158%)两个指标上均排名第一.[局限]使用的测度指标需要一定的引文积累,可能无法有效选出学者新近做出的重要工作.[结论]所提论文代表作遴选方法具备可行性.
Selecting Representative Papers Based on Innovation and Influence
[Objective]This study proposes a new method for selecting representative papers,considering their innovation and impact.[Methods]First,we designed a representative index based on each paper's innovation and influence measurement.Then,we chose papers with higher representative indices as a scholar's representative works.Taking Nobel Prize laureates in physics as an example,we selected their representative papers.We used the average ranking and precision as evaluation metrics to assess the effectiveness of the proposed model.We also analyzed Academician Zhang Tao and Professor Hirsch JE's works using the new model and identified their representative papers.[Results]Compared with the other six methods,the proposed model ranks first in both average ranking(2.838)and precision(63.158%).[Limitations]Our metrics require citation accumulation and may not effectively identify a scholar's recent contributions.[Conclusions]The proposed method is feasible for selecting representative papers.

Representative PapersSelection of Representative WorksInnovationInfluenceBasic Research Talents

刘佳程、马廷灿、岳名亮

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中国科学院武汉文献情报中心 武汉 430071

中国科学院大学信息资源管理系 北京 100190

科技大数据湖北省重点实验室 武汉 430071

论文代表作 代表作遴选 创新性 影响力 基础研究人才

中国科学院战略研究与决策支持系统建设专项中国科学院青年人才专项(青年创新促进会)

GHJ-ZLZX-2021-22-22019176

2024

数据分析与知识发现
中国科学院文献情报中心

数据分析与知识发现

CSTPCDCSSCICHSSCD北大核心EI
影响因子:1.452
ISSN:2096-3467
年,卷(期):2024.8(4)
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