engleski

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.

Algorithm design and analysis ; Approximation algorithms ; Collaboration ; Context ; Recommender systems ; Videos ; YouTube

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