One drawback of collaborative filtering (CF) is that:
A) it does not work well for a single product category.
B) it needs a large sample of users and content to work well.
C) it can accept inputs from only one data source at a time.
D) it is not useful for making recommendations across related as well as unrelated categories.

Question

Quizplus · Accepted Answer

Collaborative filtering algorithms rely on user behavior data to make recommendations. Therefore, they require a large sample of users and content to provide accurate recommendations. If the sample size is small, the predictions may not be reliable and personalized enough for users. The other options (A, C, and D) are not accurate because collaborative filtering can handle multiple categories, multiple sources of data, and is not limited to a single product category.

One Drawback of Collaborative Filtering (CF) Is That