KIISE Transactions on Computing Practices (정보과학회 컴퓨팅의 실제 논문지)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Research Capability Enhancement System Based on Prescriptive Analytics

지시적 분석 기반 역량 강화 시스템

  • 김장원 (한국과학기술정보연구원 컴퓨터지능연구실) ;
  • 정한민 (한국과학기술정보연구원 컴퓨터지능연구실) ;
  • 정도헌 (한국과학기술정보연구원 컴퓨터지능연구실) ;
  • 송사광 (한국과학기술정보연구원 컴퓨터지능연구실) ;
  • 황명권 (한국과학기술정보연구원 컴퓨터지능연구실)
  • Received : 2014.09.04
  • Accepted : 2014.11.19
  • Published : 2015.01.15
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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.

폭발적으로 증가하는 데이터와 급변하는 기술적 발전은 과거와 현재를 넘어 미래를 예견하고 대응할 수 있는 새로운 분석 패러다임을 요구한다. 지시적 분석은 목표를 설정하고 이를 달성하기 전략을 수립함으로써 분석 결과의 제시에 그치는 게 아니라 사용자에게 목표 달성을 위한 구체적 행동과 그 결과를 요구한다는 점에서 기존의 기술적 분석, 예측적 분석과 근본적인 차이점을 보여준다. 그렇지만, 아직까지 구체적인 구현 방안이 널리 연구되고 있지 않고 있다. 본 연구에서는 연구 역량 강화를 목적으로 개발되고 있는 InSciTe Advisory 사례를 통해 고려할 사항과 어떤 개발 요소들이 필요한 지를 살펴봄으로써 해당 연구 분야의 기반을 제시하고자 한다. InSciTe Advisory 시스템은 5W1H 방법론을 중심으로 연구자가 롤 모델 그룹에 도달하기 위한 전략을 수립할 수 있음을 보이며, 평가 모델을 통해 Elsevier SciVal과 비교하여 126.5%라는 비교 우위적 평가 결과를 얻었다.

Keywords

Acknowledgement

Grant : 초고성능컴퓨팅기반 국가현안대응체계 구축

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