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http://dx.doi.org/10.5626/KTCP.2015.21.1.46

Research Capability Enhancement System Based on Prescriptive Analytics  

Gim, Jangwon (KISTI)
Jung, Hanmin (KISTI)
Jeong, Do-Heon (KISTI)
Song, Sa-Kwang (KISTI)
Hwang, Myunggwon (KISTI)
Publication Information
KIISE Transactions on Computing Practices / v.21, no.1, 2015 , pp. 46-51 More about this Journal
Abstract
The explosive growth of data and the rapidly changing technical social evolution new analysis paradigm for predicting and reacting the future the past and present ig data. Prescriptive analysis has a fundamental difference because can support specific behaviors and results according to user's goals with defin researchers establish judgments and activities achiev the goals. However research methods not widely implemented and even the terminology, Prescriptive analysis, is still unfamiliar. This paper thus propose an infrastructure in the prescriptive analysis field with key considerations for enhancing capability of researchers through a case study based on InSciTe Advisory developed with scientific big data. InSciTe Advisory system s developed in 2013, and offers a prescriptive analytics report which contains various As-Is analysis results and To-Be analysis results 5W1H methodology. InSciTe Advisory therefore shows possibility strategy aims to reach a target role model group. Through the availability and reliability of the measurement model the evaluation results obtained relative advantage of 118.8% compared to Elsevier SciVal.
Keywords
prescriptive analytics; research capability enhancement model; artificial solution; InSciTe advisory; predictive analytics;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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