Social Network based Sensibility Design Recommendation using {User - Associative Design} Matrix

소셜 네트워크 기반의 {사용자 - 연관 디자인} 행렬을 이용한 감성 디자인 추천

  • Jung, Eun-Jin (Intelligent System Lab., Dept. of Computer Information Engineering, Sangji University) ;
  • Kim, Joo-Chang (Intelligent System Lab., Dept. of Computer Information Engineering, Sangji University) ;
  • Jung, Hoill (Intelligent System Lab., Dept. of Computer Information Engineering, Sangji University) ;
  • Chung, Kyungyong (School of Computer Information Engineering, Sangji University)
  • 정은진 (상지대학교 컴퓨터정보공학과 지능시스템연구실) ;
  • 김주창 (상지대학교 컴퓨터정보공학과 지능시스템연구실) ;
  • 정호일 (상지대학교 컴퓨터정보공학과 지능시스템연구실) ;
  • 정경용 (상지대학교 컴퓨터정보공학부)
  • Received : 2016.06.24
  • Accepted : 2016.08.20
  • Published : 2016.08.28


The recommendation service is changing from client-server based internet service to social networking. Especially in recent years, it is serving recommendations with personalization to users through crowdsourcing and social networking. The social networking based systems can be classified depending on methods of providing recommendation services and purposes by using memory and model based collaborative filtering. In this study, we proposed the social network based sensibility design recommendation using associative user. The proposed method makes {user - associative design} matrix through the social network and recommends sensibility design using the memory based collaborative filtering. For the performance evaluation of the proposed method, recall and precision verification are conducted. F-measure based on recommendation of social networking is used for the verification of accuracy.


Social Network;Sensibility Design;Recommendation;Crowdsourcing;Collaborative Filtering


Supported by : 한국연구재단, 한국여성과학기술인지원센터


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