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Framework

  • A general 2-step process
    • Look for users who share the same rating patterns with the active user (the one for which the prediction is made)
    • Use the ratings of those found in step 1 to calculate a prediction
  • Item-based filtering (used in Amazon.com)
    • Build an item-to-item matrix determining the relationships between each pair of items
    • Infer the user’s taste (i.e., the prediction) using the matrix


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