Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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Method of Service Curation based on User Log Analysis

사용자 이용로그 분석에 기반한 서비스 큐레이션 방법

  • Hwang, Yun-Young (Korea Institute of Science and Technology Information) ;
  • Kim, Dou Gyun (Korea Institute of Science and Technology Information) ;
  • Kim, Bo-Ram (Korea Institute of Science and Technology Information) ;
  • Park, Seong-Eun (Korea Institute of Science and Technology Information) ;
  • Lee, Myunggyo (Korea Institute of Science and Technology Information) ;
  • Yoon, Jungsun (Korea Institute of Science and Technology Information) ;
  • Suh, Dongjun (School of Convergence & Fusion System Engineering, Kyungpook National University)
  • 황윤영 (한국과학기술정보연구원 융합서비스센터) ;
  • 김도균 (한국과학기술정보연구원 융합서비스센터) ;
  • 김보람 (한국과학기술정보연구원 융합서비스센터) ;
  • 박성은 (한국과학기술정보연구원 융합서비스센터) ;
  • 이명교 (한국과학기술정보연구원 융합서비스센터) ;
  • 윤정선 (한국과학기술정보연구원 융합서비스센터) ;
  • 서동준 (경북대학교 융복합시스템공학부)
  • Received : 2018.04.14
  • Accepted : 2018.04.27
  • Published : 2018.04.30
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Abstract

Our research team implemented and operated the system by analyzing the membership information and identifying the different preferences for each group and providing the results of the recommendation based on accumulated membership information and activity log data to the individual. The utilization log was followed up. We analyzed how many people use recommended services and analyzed whether there are any factors other than the personalization service algorithm that affect the service utilization of the system with personalization. In addition, we propose recommendation methods based on behavioral changes when incentives are given through analyzing patterns of users' usage according to methods of recommending services and contents that are often used based on analysis contents.

이 논문은 개인별 개인화 서비스 활용 로그를 추적조사 하여 개인별로 얼마나 많이 추천된 서비스를 사용하였는지 분석하고, 개인화가 적용된 시스템의 서비스 활용도에 영향을 주는 요인이 개인화 서비스 알고리즘외 다른 요인이 있는지 분석하였다. 또한, 분석 내용을 기반으로 단순히 많이 이용하는 서비스 및 콘텐츠를 추천하는 방법에 따른 사용자 이용패턴 분석을 통해 인센티브를 부여하였을 때의 행동변화에 따른 추천방법을 제안한다.

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References

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