期刊文献+

Application of Article - Level Metrics and comparison with Journal- Level Metrics in differentiated document recommendation: An empirical study in artificial intelligence field

原文传递
导出
摘要 The measurement indexes of literature include citation frequency,H index,etc.The evaluation of core joumals mainly relies on the indexes such as impact factor or comprehensive evaluation method.With the in-depth development of research,these indicators are not comprehensive and accurate for literature and jourmals.Therefore,according to various literature needs for different researchers,"core literature"in this study was divided into three types:classical,popular and frontier;and measurement system of document value was constructed with comprehensive use of entropy weight method and principal component analysis from the perspective of Article-Level Metrics.In the case study of artificial intelligence(AD),three types of document sets were acquired with the threshold value of specific indicators,and then measured by a combination of multi-index,achieving identification and recommendation of core documents for different research needs.At the same time,this paper further calculates the total score of the joumals according to the literature score,and finds that the journal distribution of different types of core literature is quite different.The difference between the ranking of joumal scores and the ranking of impact factor after literature classification is relatively large,but the ranking of jourmal normalized Eigenfactor and the ranking of impact factor are similar.These research directions,loading joumals,selected indicators,and temporal effects in three types of core documents were revealed in the study,which can provide a certain reference for promoting scientific research in AI and launching scientific research management services.
出处 《Data Science and Informetrics》 2021年第4期84-97,共14页 数据科学与信息计量学(英文)
基金 This research is funded by Bejing Social Science Fund(grant number 19GLC057) Project of High-level Teachers in Beijing Municipal Universities-Youth Top-notch Talent Support Program(grant number PXM2020_014204_000019).
  • 相关文献

参考文献5

二级参考文献171

共引文献293

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部