Video Suggestion and Discovery for YouTube: Taking Random Walks Through the View Graph
| Citations: | 20 - 0 self |
BibTeX
@MISC{Baluja_videosuggestion,
author = {Shumeet Baluja and Rohan Seth and D. Sivakumar and Yushi Jing and Jay Yagnik and Shankar Kumar and Deepak Ravich and Ran Mohamed Aly},
title = {Video Suggestion and Discovery for YouTube: Taking Random Walks Through the View Graph},
year = {}
}
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Abstract
The rapid growth of the number of videos in YouTube provides enormous potential for users to find content of interest to them. Unfortunately, given the difficulty of searching videos, the size of the video repository also makes the discovery of new content a daunting task. In this paper, we present a novel method based upon the analysis of the entire user–video graph to provide personalized video suggestions for users. The resulting algorithm, termed Adsorption, provides a simple method to efficiently propagate preference information through a variety of graphs. We extensively test the results of the recommendations on a three month snapshot of live data from YouTube.
