Prediction of Research Topics on Science & Technology (S&T) using Ensemble Forecasting
نویسندگان
چکیده
Proper resource allocation on research requires accurate forecasting for the future research activities. Forecasting task can be done using judgmental or numerical analysis. Bibliometric analysis is a quantitative method to determine the trend of research area by counting the frequency of certain keywords using journal publication or patents. This paper reports the implementation of our new forecast combination method which selects the best methods used by similar validation dataset on Indonesian journal database, namely the Garuda dataset, especially on the subject of Science and Technology. The experimental result indicates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, the emerging research topics for the next few years can be objectively identified.
منابع مشابه
Prediction of Research Topics Using Ensemble of Best Predictors from Similar Dataset
Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed ...
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