图书情报工作 ›› 2020, Vol. 64 ›› Issue (6): 138-145.DOI: 10.13266/j.issn.0252-3116.2020.06.016

• 综述述评 • 上一篇    下一篇

学术论文引用预测研究进展

夏琬钧1,2, 陈晓红1, 江艳萍1   

  1. 1. 西南交通大学图书馆 成都 611756;
    2. 西南交通大学信息科学与技术学院 成都 611756
  • 收稿日期:2019-07-02 修回日期:2019-09-19 出版日期:2020-03-20 发布日期:2020-03-20
  • 作者简介:夏琬钧(ORCID:0000-0001-9722-9837),馆员,博士研究生,E-mail:xiawanjun@home.swjtu.edu.cn;陈晓红(ORCID:0000-0003-3277-8725),副研究馆员,硕士;江艳萍(ORCID:0000-0003-3152-0204),馆员,博士。
  • 基金资助:
    本文系四川省文化和旅游厅图书情报学与文献学规划项目"基于学术大数据的潜力学者挖掘研究"(项目编号:WHTTSXM[2018]25)和四川省社会科学重点研究基地-四川学术成果分析与应用研究中心项目"基于在线评论的中文图书影响力研究"(项目编号:SCAA17-006)研究成果之一。

Research on Academic Paper Citation Prediction

Xia Wanjun1,2, Chen Xiaohong1, Jiang Yanping1   

  1. 1. Library of Southwest Jiaotong University, Chengdu 611756;
    2. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756
  • Received:2019-07-02 Revised:2019-09-19 Online:2020-03-20 Published:2020-03-20

摘要: [目的/意义] 对学术论文引用预测影响因素和预测方法进行梳理,分析现存问题并提出发展方向。[方法/过程] 采用文献调研法,综述国内外研究进展,总结预测影响因素和预测方法的相关内容和特点。[结果/结论] 现有影响因素指标繁多,无统一标准;预测方法理论基础薄弱;引文预测动态性研究不足;预测模型通用性受限。未来应加强引文预测的理论研究、加强传统文献计量和替代计量的结合、加强自然语言处理的深度应用、建立统一的基线标准、构建更加精准的预测模型。

关键词: 引用预测, 影响因素, 预测方法

Abstract: [Purpose/significance] This paper summarizes the influencing factors and prediction methods of academic paper citation, analyzes the existing problems and proposes the future development directions.[Method/process] This paper used the literature research method to review the research progress of academic papers at home and abroad, and summarized the relevant content and characteristics of influencing factors and prediction methods.[Result/conclusion] There are many indicators of influencing factors, but there is no unified selection criteria. The theoretical basis of prediction methods is weak. The research on dynamics of citation prediction is insufficient. The generality of prediction models is limited. In the future, we should strengthen the theoretical research of citation prediction methods, the combination of traditional bibliometrics and alternative metrics, the deep application of natural language processing, and establish a unified baseline standard, a more accurate prediction model.

Key words: citation prediction, influencing factor, prediction method

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