A Video Recommendation Algorithm Based on Hyperlink-Graph Model

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2. Classical Graph-Based Recommendation Algorithm

The classical graph-based recommendation algorithm (Li, Su & Wang, 2012) mainly depends on constructing a resource allocation matrix over a graph and following the random walk algorithm. The detailed description is as follows:

• Step 1.

  Build a bipartite graph. Assume that there are U users and N videos in the recommendation system. The system can be expressed by a U+N nodes bipartite graph. It can be described as Figure 1.

• Step 2.

  Construct the metric matrix. This process includes two parts. One is resource allocation from videos to videos. The other is resource allocation from user to videos. The resource allocation weight from video j to user i can be described as follows:

  
  (1)

where, D_j means how many users browse video j. D_k is the number of videos that user k has ever browsed. Hence, the metric matrix is a square matrix .