한국인터넷방송통신학회논문지 (The Journal of the Institute of Internet, Broadcasting and Communication)

  • 제12권4호
  • /
  • Pages.95-102
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  • 2012
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  • 2289-0238(pISSN)
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  • 2289-0246(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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PCA와 NMF를 이용한 대화식 드라마의 스토리 경로 추천 시스템 구현

An Implementation of Story Path Recommendation System of Interactive Drama Using PCA and NMF

  • 이연창 (을지대학교 의료IT마케팅학과) ;
  • 장재희 (을지대학교 의료IT마케팅학과) ;
  • 김명관 (을지대학교 의료IT마케팅학과)
  • 투고 : 2012.06.01
  • 심사 : 2012.08.10
  • 발행 : 2012.08.31
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초록

대화식 드라마는 사용자의 자유로운 선택과 참여가 요구되는 상호작용성을 가진 이야기를 말한다. 본 논문에서는 이러한 대화식 드라마의 특성을 이용하여 훈련 데이터를 만들어 사용자의 선호도를 파악한다. 그 후 파악된 선호도 특성에 맞게 새로운 사용자들에게 스토리의 경로를 추천하는 시스템 구현 과정을 기술한다. 선호도 특성을 추출하기 위하여 Principal Component Analysis(이하 PCA)와 Non-negative Matrix Factorization(이하 NMF)를 사용하였다. PCA를 이용하여 추천한 결과 성공률은 75%, NMF을 이용하여 추천한 결과 성공률은 62.5%를 나타냈다.

Interactive drama is a story which requires user's free choice and participation. In this study, we grasp user's preference by making training data that utilize characters of interactive drama. Furthermore, we describe process of implementing systems which recommend new users path of stories that correspond with their preference. We used PCA and NMF to extract characteristic of preference. The success rate of recommending was 75% with PCA, while 62.5% with NMF.

키워드

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