基于区间数据分析的各学科期刊发展现状研究  

Research on the Present Conditions of Journals from Different Disciplines Based on Interval Data Analysis

作　　者：王岩[1] 张寅[2,3] 王惠文[2,3] 

机构地区：[1]国家自然科学基金委员会计划局,北京100085 [2]北京航空航天大学经济管理学院,北京100191 [3]北京航空航天大学复杂数据分析研究中心,北京100191

出　　处：《数理统计与管理》2012年第1期134-141,共8页Journal of Applied Statistics and Management

基　　金：国家自然科学基金项目(J0824301);国家自然科学基金重点项目(71031001);国家自然科学基金创新研究群体科学基金项目(70821061);国家自然科学基金项目(70771004)

摘　　要：由于学科的自身特点和统计源的学科结构特点,不同学科期刊具有显著差异。但由于期刊数量庞大,评价指标多种多样,很难从宏观上把握各学科期刊的整体特点,对学科间差异给出科学的判断。本文以SCI期刊为研究对象,用区间数据代表各学科期刊,采用因素区间数据PCA算法探寻反映期刊水平的关键指标,并利用区间数据投影的方式绘制主平面图,反映各学科期刊的整体特点及我国期刊在国际上的地位。Due to different characteristics of disciplines and different structures of databases, journals from different disciplines vary widely in the bibliometric indexes. However, it is difficult to obtain a general overview of the development of each discipline and to explore the differences between different disciplines, since there exists a huge number of journals featured by a variety of indicators. This paper packs Chinese SCI journals from the same discipline into an interval-valued observation, and performs Factor Interval Data Analysis on all the observations to find out the key indicator that accurately describes development condition of journals. The plane of first two factor is then displayed to show the current status of journals from different disciplines. It also helps describe how well Chinese SCI journals perform in the international sphere.

关 键 词：学科发展现状 区间数据 因素区间数据PCA算法 主平面图 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O212[自动化与计算机技术—控制科学与工程]