Collaborative Filtering Using Associative Neural Memory

  title={Collaborative Filtering Using Associative Neural Memory},
  author={Chuck P. Lam},
There are two types of collaborative filtering (CF) systems, user-based and item-based. This paper introduces an item-based CF system for ranking derived from Linear Associative Memory (LAM). LAM is an architecture that is founded on neuropsychological principles and is well studied in the neural network community. We show that our CF system has a user-based interpretation. Given a random subset of all users, our CF system is an unbiased estimator of predictions made from all users. We further… CONTINUE READING

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