Video Recommendation Probability and Product Trade-offs
Scenario
A video-recommendation system selects K distinct videos for each user from an inventory of N distinct videos (sampling without replacement per user). Two friends are each shown K videos from the same inventory. We assume selections for different users are independent (the inventory is not globally depleted across users).
Questions
-
If K videos are randomly chosen from N distinct videos, what is the probability that a particular video appears in the set?
-
Two friends each receive K videos (without replacement within a user) from the same inventory. What is the probability they share at least one identical video?
-
Should we push identical videos to friends or diversify their feeds? Discuss expected engagement impact and trade-offs.
Hints
-
Use combinations and complementary probabilities.
-
Connect the calculations to user engagement reasoning.