论文信息 - Recommendation of YouTube Videos

Recommendation of YouTube Videos

YouTube is a huge video-sharing service with hundreds of millions of users and hundreds of thousands of videos being uploaded every day. Thus, recommendation of YouTube videos to a single user is a challenging problem which cannot be solved by simply reusing the prevailing recommendation methods. The paper presents a specific recommendation algorithm for YouTube which relies on the data retrieved through the YouTube Data API. A cloud-based application integrates the proposed algorithm and offers a web interface to end users. The paper presents a preliminary analysis of the recommendation quality and lists YouTube Data API limitations which influence the design of recommender systems for YouTube videos.

Ivana Podnar Zarko | Maria Brbic | Eugen Rozic

[1] Gediminas Adomavicius,et al. Incorporating contextual information in recommender systems using a multidimensional approach , 2005, TOIS.

[2] George Karypis,et al. Item-based top-N recommendation algorithms , 2004, TOIS.

[3] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.