Question 1 of 30
A retail company is implementing a recommendation engine to enhance customer experience on its e-commerce platform. The engine uses collaborative filtering based on user behavior and item similarity. If the company has 1000 users and 5000 items, and each user has rated an average of 20 items, what is the sparsity of the user-item interaction matrix? How does this sparsity impact the effectiveness of the recommendation engine?
The sparsity is 0.996, which can lead to challenges in generating accurate recommendations due to insufficient data.
The sparsity is 0.95, indicating a well-populated matrix that supports effective recommendations.
The sparsity is 0.8, suggesting that the recommendation engine will perform optimally.
The sparsity is 0.5, which means the recommendation engine will have ample data to work with.

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