引用本文:陈颖瑜,邓小茹.数据科学驱动下ESI潜力学科入围预测方法的实践探索[J].中华医学图书情报杂志,2019,28(8):35-40.
数据科学驱动下ESI潜力学科入围预测方法的实践探索
Data science-driven prediction of ESI-covered potential subjects
DOI:10.3969/j.issn.1671-3982.2019.08.005
中文关键词:  ESI学科  “暗数据”可视化  文献计量学  趋势预测  回归分析
英文关键词:ESI-covered subjects  "Dark data" visualization  Bibliometrics  Trend prediction  Regression analysis
基金项目:广东省教育厅“2017年广东高校省级重点平台和重大科研项目”特色创新(自然科学类)资助项目“‘暗数据’可视化在高水平大学 ESI 学科发展的动态跟踪及预测研究”(2017KTSCX156)的研究成果之一
作者单位
陈颖瑜 广州医科大学图书馆广东 广州 511436 
邓小茹 广州医科大学图书馆广东 广州 511436 
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中文摘要:
      为研究“双一流”建设过程中ESI潜力学科入围全球前1%的预测方法与“暗数据”可视化分析思路的耦合关系,定期抓取与追踪ESI学科数据,合并使用WOS-SCIE、InCites、ESI、SQL数据库,联用SWOT分析法、文献调研法和回归分析法等,实现机构学科潜力全景分析,构建潜力学科入围所需论文篇数的线性预测公式,并分别从绝对指标和相对指标的不同维度搭建入围预测的绝对指标和相对指标2个数据模型,尝试对ESI潜力学科进行趋势预测,拟归纳合理或通用的预测方法,以期进一步挖掘未来的潜力学科。
英文摘要:
      A linear prediction formula of papers for ESI-covered potential subjects was established by regularly capturing and searching the ESI-covered subject data from WOS-SCIE, InCites, ESI and SQI Databases respectively, and analyzing the institutional subject potential by SWOT analysis, literature analysis and regression analysis respectively in order to study the coupling relationship between the prediction methods of global top 1% ESI-covered potential subjects and the visual analysis methods of "dark data" during the construction of " first class universities and first class of subjects". An absolute index model and a relative index model were established for predicting ESI-covered potential subjects. The trend of ESI-covered potential subjects was predicted, and the rational or general methods for predicting ESI-covered potential subjects were summarized in order to further mine the future potential subjects.
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