2013 Volume 25 Issue 1 Pages 624-635
YouTube as the most popular video hosting service is growing rapidly, making it difficult for users to ?nd video that fit their particular interest. Implementation of video recommendation method is one way to solve this problem. However, several difficulties remain, one of them is no clear relation between the original and recommended video. Moreover, there are many cases that the recommended videos mostly have similar contents to the original videos. In this paper, we try to solve these problems by concept of words and to explicitly state the reason for recommendation. We build video recommendation application for YouTube using Formal Concept Analysis, and we performed the experiments to evaluate our system. By analyzing the results of experiments, we look at the effect of our system on user's load.
