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Design of Customized Research Information Service Based on Prescriptive Analytics

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2022, 8(3), pp.69-74
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : March 29, 2022
  • Accepted : April 27, 2022
  • Published : June 30, 2022

Jeong-Won Lee 1 Yong sun Oh 1

1목원대학교

Accredited

ABSTRACT

Big data related analysis techniques, the prescriptive analytics methodology improves the performance of passive learning models by ensuring that active learning secures high-quality learning data. Prescriptive analytics is a performance maximizing process by enhancing the machine learning models and optimizing systems through active learning to secure high-quality learning data. It is the best subscription value analysis that constructs the expensive category data efficiently. To expand the value of data by collecting research field, research propensity, and research activity information, customized researcher through prescriptive analysis such as predicting the situation at the time of execution after data pre-processing, deriving viable alternatives, and examining the validity of alternatives according to changes in the situation Provides research information service.

Citation status

* References for papers published after 2022 are currently being built.