한국게임학회 논문지 (Journal of Korea Game Society)

  • 제15권4호
  • /
  • Pages.59-68
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  • 2015
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  • 1598-4540(pISSN)
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  • 2287-8211(eISSN)
한국게임학회 (Korea Game Society)
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Data Mining을 이용한 전략시뮬레이션 게임 데이터 분석

A Study of Analyzing Realtime Strategy Game Data using Data Mining

  • 용혜련 (한림대학교 인터랙션 디자인 대학원) ;
  • 김도진 (한림대학교 인터랙션 디자인 대학원) ;
  • 황현석 (한림대학교 경영학부)
  • 투고 : 2015.07.08
  • 심사 : 2015.08.10
  • 발행 : 2015.08.20
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초록

정보통신기술의 발달로 빅데이터 분석을 통해 사람들 일상의 기록과 잠재적 요구까지 통찰할 수 있게 되었으며, 우리의 일상 속에서 방대한 정보를 실시간으로 도출하고 있다. 여러 산업이나 기업에서 이미 빅데이터와 결합시켜 비즈니스 등 다양한 분야에 활용하고 있지만 게임 산업에서의 빅데이터 활용은 아직까지 미흡한 실정이다. 이에 본 연구에서는 데이터 마이닝을 기법을 적용하여 전략시뮬레이션 게임 데이터를 분석하였다. 전략시뮬레이션 게임 데이터를 Decision Tree, Random Forest, Multi-class SVM, Linear Regression 분석 기법을 적용하여 게임 유저의 게임수준에 영향을 미치는 요인을 분석하였다. 게임수준을 예측하는데 있어 가장 우수한 성능을 보인 기법과 변수들을 도출하여 게임 디자인과 사용성을 증대시키기 위한 제안을 하고자 한다.

The progress in Information & Communication Technology enables data scientists to analyze big data for identifying peoples' daily lives and tacit preferences. A variety of industries already aware the potential usefulness of analyzing big data. However limited use of big data has been performed in game industry. In this research, we adopt data mining technique to analyze data gathered from a strategic simulation game. Decision Tree, Random Forest, Multi-class SVM, and Linear Regression techniques are used to find the most important variables to users' game levels. We provide practical guides for game design and usability based on the analyzed results.

키워드

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