Which machine learning approach is NOT commonly used in major streaming services' recommendation algorithms for suggesting films and TV shows to viewers?

In today's competitive streaming landscape, personalization algorithms have become the backbone of viewer retention and engagement. Major streaming platforms invest millions in fine-tuning these systems to keep viewers watching longer. This trivia question explores how these sophisticated recommendation engines actually work behind the scenes. Test your knowledge about the technology that shapes what millions of viewers see on their screens every day!

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Natural Language Processing (NLP) for analyzing viewer reviews and content descriptions
Blockchain-based distributed consensus algorithms for viewer preference validation
Collaborative filtering based on viewing patterns of similar users
Content-based filtering analyzing metadata like genre, actors, and directors