정보과학회 논문지 (Journal of KIISE)

  • 제42권5호
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  • Pages.664-670
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  • 2015
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  • 2383-630X(pISSN)
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  • 2383-6296(eISSN)
한국정보과학회 (Korean Institute of Information Scientists and Engineers)
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사용자의 소셜 카테고리를 이용한 유튜브 동영상 추천 알고리즘

The YouTube Video Recommendation Algorithm using Users' Social Category

  • 유소엽 (가천대학교 소프트웨어설계경영학과) ;
  • 정옥란 (가천대학교 소프트웨어학과)
  • 투고 : 2015.01.09
  • 심사 : 2015.03.07
  • 발행 : 2015.05.15
⟨ 이전 논문 다음 논문 ⟩

초록

인터넷과 스마트폰의 발전과 함께 소셜 미디어 공유 사이트인 유튜브도 크게 성장하여 수많은 동영상을 공유하는 사이트가 됐다. 사용자들이 유튜브를 통해 동영상을 공유하면서 소셜 데이터를 만들어내고, 많은 동영상들 중에서 본인의 관심사가 반영된 동영상 추천을 원하게 된다. 본 논문에서는 유튜브 데이터를 이용하여 사용자의 사회적 관계와 유튜브의 특징이 반영된 소셜 카테고리 분류 목록을 기반으로 사용자의 소셜 카테고리를 추출한다. 우리는 좀 더 정확하고 의미있는 추천을 위해 추출된 사용자 소셜 카테고리를 이용한 유튜브 동영상을 추천하는 알고리즘을 제안하였다. 또한 실험을 통해 그 유효성을 검증하였다.

With the rapid progression of the Internet and smartphones, YouTube has grown significantly as a social media sharing site and has become popular all around the world. As users share videos through YouTube, social data are created and users look for video recommendations related to their interests. In this paper, we extract users' social category based on their social relationship and social category classification list using YouTube data. We propose the YouTube recommendation algorithm using the extracted users' social category for more accurate and meaningful recommendations. We show experiment results of its validation.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

참고문헌

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피인용 문헌

  1. An Ensemble Method for Latent Interest Reasoning of Mobile Users vol.21, pp.11, 2015, https://doi.org/10.5626/KTCP.2015.21.11.706