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| Step | Action | |------|--------| | 1. DNA | Defined 2,300 micro-genres (e.g., "Emotional Coming-of-Age Dramas Featuring a Piano") | | 2. Data | Used 100M user rating events + skip data as implicit training labels | | 3. Pattern | Trained matrix factorization model to find user–content clusters | | 4. Validation | Held back 10% of user histories; measured rank of held-out films | | 5. Adaptation | Daily online learning to incorporate new uploads |

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