CAJ | 학술논문

国内外学者开展了若干借助文献计量指标来识别和预测重要科技奖项得主的研究与实践，但已有研究大多局限于对少数几项文献计量指标进行简单的计量统计，对问题的揭示不够全面和深入。利用支持向量机对图灵奖得主和非图灵奖得主的多项文献计量指标进行了分析，在两种不同情境下借助支持向量机对样本数据进行分类学习并进行识别与预测，发现利用文献计量指标建立的支持向量机模型对图灵奖得主具有很好的识别能力，但预测能力一般。
국내외학자개전료약간차조문헌계량지표래식별화예측중요과기장항득주적연구여실천，단이유연구대다국한우대소수궤항문헌계량지표진행간단적계량통계，대문제적게시불구전면화심입。이용지지향량궤대도령장득주화비도령장득주적다항문헌계량지표진행료분석，재량충불동정경하차조지지향량궤대양본수거진행분류학습병진행식별여예측，발현이용문헌계량지표건립적지지향량궤모형대도령장득주구유흔호적식별능력，단예측능력일반。
Researchers have explored the use of bibliometric indicators to identify and predict the winners of some prominent science a-wards. Previous work mainly employed some preliminary bibliometrics and statistics, lacking coverage of bibliometric indicators and depth of analysis. In order to investigate the identifiability and predictability of Turing Award winners, 20 bibliometric indicators about 33 Turing Award winners and 300 non-Turing Award winners were analyzed. A classification and prediction analysis was conducted with the biblio-metric indicators and data by support vector machine( SVM) in two different scenarios. The result indicated that a classification model could be developed based on bibilometric indicators to identify the Turing Award winners with a high precision. However, the prediction precision appeared medium.