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《Journal of Intelligence》 2015-02
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Study on the Identifiability and Predictability of Turing Award Winners Based on Multiple Bibliometric Indicators and Support Vector Machine

Tang Chuan;Tang Juan;Fang Junmin;Liu Chunjiang;Chengdu Documentation and Information Center,Chinese Academy of Sciences;Chengdu Information Technology of Chinese Academy of Sciences Co,Ltd.;  
Researchers have explored the use of bibliometric indicators to identify and predict the winners of some prominent science awards.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 bibliometric 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.
【CateGory Index】: G353.1
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