WWW2008 Refereed Papers - WWW 2008: Refereed Papers
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Refereed Papers

Track: Industrial Track Session

Paper Title:
Video Suggestion and Discovery for YouTube: Taking Random Walks Through the View Graph


  • Shumeet Baluja(Google Inc.)
  • Rohan Seth(Google Inc.)
  • D. Sivakumar(Google Inc.)
  • Yushi Jing(Google Inc.)
  • Jay Yagnik(Google Inc.)
  • Shankar Kumar(Google Inc.)
  • Deepak Ravichandran(Google Inc.)
  • Mohamed Aly(University of Pittsburgh)

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.

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