exploration

New users and new items have zero interaction history, so collaborative filtering has nothing to work with. The candidates who pass treat it as a lifecycle, not a single trick. Here is how.

A recommender trains on data its own past recommendations produced, so it learns to confirm its own beliefs. The signal is recognizing the loop, naming the biases it breeds, and knowing the exploration and debiasing fixes that break it.