期刊文献+

基于FIS模型的学者学术代表作遴选研究

Research on Selection of Representative Works of Scholars Based on FIS Model
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摘要 [目的/意义]在“大力推行优秀成果和代表作评价”的背景下,如何科学地遴选学术代表作是摆在所有学者面前的一个重要研究问题,尤其是一般学者的代表作遴选更加值得关注。[方法/过程]在阐述了模型构建基本思想的基础上,文章从期刊影响因子、即时被引频次和内容相似度三个方面构建了适合一般学者代表作遴选的FIS模型。利用陕西省自然科学优秀论文获得者的学术论文进行学术代表作遴选实证研究,并从内部和外部两个方面进行了对比分析。[结果/结论]构建的FIS模型具有一定的比较优势和实际意义,能够更科学地遴选代表作,在一定程度上有助于推动学术繁荣和进步。 [Purpose/significance]It is an important task that scholars reasonably select academic representative works,especially for general scholars,under the background of“vigorously promoting the evaluation of outstanding achievements and representative works”.[Method/process]After elaborating the theoretical basis of model construction,this paper constructs a FIS model suitable for the selection of representative works of general scholars from three aspects:journal impact factor,immediately cited frequency and context similarity.Then,this paper makes an empirical study on the selection of academic representative works by using the academic papers of the winners of natural science excellent papers in Shaanxi Province.In addition,the comparative analysis is carried out from two aspects of internal and external comparison.[Result/conclusion]The results proved that the model constructed in this paper has certain comparative advantages and practical significance.The FIS model can better select representative works,and it can help promote academic prosperity and progress to a certain extent.
作者 闫晓慧 张逸勤 杨文霞 巩洪村 邓三鸿 Yan Xiaohui;Zhang Yiqin;Yang Wenxia;Gong Hongcun;Deng Sanhong(School of Information Management,Nanjing University,Jiangsu Nanjing 210023;Jiangsu Province Key Laboratory of Data Engineering and Knowledge Service,Jiangsu Nanjing 210023)
出处 《情报理论与实践》 CSSCI 北大核心 2024年第9期99-106,共8页 Information Studies:Theory & Application
基金 国家社会科学基金项目“大数据环境下学术成果真实价值与影响的实时预测及长期评价研究”(项目编号:19BTQ062) 江苏省研究生实践创新计划(项目编号:SJCX23_0008)的成果之一。
关键词 学术代表作 学者评价 影响因子 即时被引频次 内容相似度 academic representative works scholar evaluation impact factor immediately cited frequency content similarity
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