Slide 8
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Why graphs for recommender systems?
• Graph = matrix: edge(u,v) = M[u,v]
– Note: always sparse graphs
• Intuitive, human-understandable representation
– Easy to visualize and explain.
• Unifies collaborative filtering (typically matrix
based) with recommendation in social networks.
– Random walk algorithms.
• Local view à vertex-centric computation