Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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Fuzzy Decision Making-based Recommendation Channel System using the Social Network Database

소셜 네트워크 데이터베이스를 이용한 퍼지 결정 기반의 추천 채널 시스템

  • Ma, Linh Van (School of Electronics and Computer Engineering, Chonnam National University) ;
  • Park, Sanghyun (School of Electronics and Computer Engineering, Chonnam National University) ;
  • Jang, Jong-hyun (Electronics and Telecommunications Research Institute) ;
  • Park, Jaehyung (School of Electronics and Computer Engineering, Chonnam National University) ;
  • Kim, Jinsul (School of Electronics and Computer Engineering, Chonnam National University)
  • Received : 2016.08.12
  • Accepted : 2016.10.10
  • Published : 2016.10.31
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Abstract

A user usually gets the same suggesting results as everyone else in most of the multimedia social services, nowadays. To address the challenging problem of personalization in the social network, we propose a method which exploits user's activities, user's moods, and user's friend relationships from the social network to build a decision-making system. Depending on a current state of the user's mood, this system infers the most appropriated video for the user. In the system, the user evaluates a set of the given recommendation methods which extract from the user's database social network and assigns a vague value to each method by a weight. Then, we find the fuzzy collection solution for the system and classify the set of methods into subsets, and order the subsets based on its local dominance to choose the best appropriate method. Finally, we conduct an experiment using the YouTube API with a lot of video types. The experiment result shows that the channel recommendation system appropriately affords the user's character, it is more satisfying than the current YouTube based on an evaluation of several users.

사용자는 일반적으로 멀티미디어 소셜 서비스로부터 다른 사람들과 같은 결과를 제공받는다. 따라서 소셜 네트워크 안에 개인의 어려운 문제를 해결하기 위해 본 논문에서는 의사 결정 시스템 구축을 사용자의 활동, 사용자의 기분과 소셜 네트워크를 통한 사용자의 친구 관계 정보를 활용하는 방법을 제안한다. 사용자의 현재 기분 상태에 따라 시스템은 사용자에게 가장 적합한 영상을 유추한다. 이 시스템은 사용자가 이용하는 소셜 네트워크 데이터베이스에서 추출한 추천 방법의 집합을 측정하고, 가중치에 따라 모호한 값이 각각의 방법에 할당한다. 본 논문에 시스템에서는 퍼지 수집 솔루션을 찾아서 하위 집합들로 방법들을 분류하고, 가장 적절한 방법을 선택하기 위해 퍼지로직을 기반으로 상기 하위 집합을 결정한다. 마지막으로, YouTube API와 다양한 영상을 이용하여 시뮬레이션 실험을 진행하였다. 이 실험에서 채널 추천 시스템은 사용자 특성에 맞는 적절한 결과를 보여주며, 이것은 여러 사용자의 평가에 기반하는 현재 유투브 보다 더 좋은 만족감을 준다.

Keywords

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