Explain Collaborative Filtering.

1.	Explain Collaborative Filtering.
Answer» Based on user behavioral data, COLLABORATIVE filtering (CF) creates a recommendation system. By analyzing data from other users and their interactions with the system, it filters out INFORMATION. This method assumes that people who agree in their EVALUATION of particular items will likely agree again in the future. Collaborative filtering has three major components: users- items- interests. EXAMPLE: Collaborative filtering can be SEEN, for instance, on online shopping sites when you see phrases such as "recommended for you”.

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