Collaborative Filtering and Recommendation Systems
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Questions and Answers

In collaborative filtering, what is the goal of recommending items to customers?

  • To recommend items randomly to increase diversity
  • To recommend items that have previously been purchased by similar customers (correct)
  • To recommend items based on their popularity
  • To recommend items based on users who are most different
  • What similarity measure does Amazon use in generating recommendations?

  • Pearson correlation
  • Euclidean distance
  • Cosine similarity (correct)
  • Jaccard index
  • What kind of data does Amazon use to generate recommendations?

  • Only product features
  • Only user demographic data
  • Both user demographic data and product features
  • Only user interaction data without looking at features (correct)
  • Which users are considered more similar in collaborative filtering?

    <p>Users who have rated some different items but also rated the same items</p> Signup and view all the answers

    What is the binary representation of items purchased by user u?

    <p>R*.</p> Signup and view all the answers

    In the context of defining similarity between users and items, what does 𝑅.,+ represent?

    <p>Item representation (I)</p> Signup and view all the answers

    How is the best case scenario defined for similarity scores in terms of Euclidean distance?

    <p>When users i and j buy the same item</p> Signup and view all the answers

    What defines the Euclidean distance between two items i and j in this context?

    <p>R*,+ - R.,</p> Signup and view all the answers

    What is the purpose of subtracting the average rating by user v from each rating in the formula for Pearson correlation similarity between users?

    <p>To eliminate the effect of below-average ratings on the similarity calculation</p> Signup and view all the answers

    How does the cosine similarity differ from Pearson correlation similarity in terms of item consideration?

    <p>Cosine similarity considers all items while Pearson correlation only focuses on shared items.</p> Signup and view all the answers

    Why is it important to consider only shared items when determining similarity between users based on ratings?

    <p>To ensure users are maximally similar if they rate shared items the same way</p> Signup and view all the answers

    In the context of recommendation systems, what is the purpose of Euclidean distance in relation to similarities between items?

    <p>To measure the closeness or similarity between items based on their ratings</p> Signup and view all the answers

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