Web video recommendation and long tail discovering

Given countless web videos available online, one problem is how to help users find videos to their taste in an efficient way. In this paper, to facilitate user’s browsing we propose relevant and exploratory recommendation algorithms utilizing multimodal similarity and contextual network to organize web videos of various topics. Comparison experiments demonstrate proposed approach generates more accurate video relevancy. And our method is more flexible in discovering user latent interests in long tail videos.