In developing a recommendation system, how would collaborative filtering be implemented, and what challenges might arise?
- By analyzing only the content of the items
- By analyzing only user behavior without considering items
- By ignoring user preferences
- By leveraging user-item interactions and facing challenges such as cold start and data sparsity
Collaborative filtering uses user-item interactions to make recommendations, often facing challenges such as the cold start problem (new users/items with no interactions) and data sparsity (limited interactions available).
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