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In the paper "Item-Based Collaborative Filtering Recommendation Algorithms" In section 3.2.2 about regression, it is said the the user's actual rating of item N (Ru,n), is replaced with an estimate of that rating (R'u,n) via linear regression. The linear regression model seems to be mapping rating of the target item (i) to ratings of the similar item which the user has also rated (N). Question is, what is input into the linear regression model for the estimate (R'u,n) to be calculated. It can not be the target user's rating of the target item (Ru,i) since that is what we are trying to predict in the first place. Is the input into the regression the target user's rating of the similar item (Ru,n)?

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    $\begingroup$ What is Ru? What is n? If you could formalize the problem without requiring us to read your particular book we could be more helpful. $\endgroup$ – Nicholas Mancuso Jan 7 '15 at 21:47
  • $\begingroup$ well you'd have to be familiar with the paper to understand the question, I've used the same terminology as the paper. It's a conference paper so not too long $\endgroup$ – soheildb Jan 7 '15 at 22:09

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