Prediction of research topics on science & technology (S&T) using ensemble forecasting

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)253-268
Number of pages16
JournalInternational Journal of Software Engineering and its Applications
Volume7
Issue number5
DOIs
Publication statusPublished - 30 Oct 2013

Keywords

  • Emerging topics
  • Ensemble
  • Forecasting
  • Research topics
  • Science & Technology (S&T)
  • Similarity measure
  • Time series

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