Practice Data Requirements (11.3) - Recommender Systems

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8 questions

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6 sample questions

Question 1.
What are the three primary types of data needed for a recommender system?
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Think about the information that defines users and items.
Question 2.
Why is item data important in recommender systems?
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Consider what features or characteristics describe an item.
3Question 3.
What types of data are needed to build a recommender system?
- User Data only
- Item Data only
- Both User and Item Data
- User, Item, and Interaction Data
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Recall the different types discussed.
4Question 4.
True or False: Interaction data includes numerical ratings and clicks.
- True
- False
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Think about examples of user engagement.
Question 5.
Imagine a recommender system that only has user data but no item data. What issues might arise in this scenario?
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Consider what information is needed to make personalized suggestions.
Question 6.
Design a strategy for addressing the cold start problem for new users in a recommender system.
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Think about quick ways to gain insight into user preferences.

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